{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nEP3HMg_s-jS"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_09_4_facial_points.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MMhyB56JCfQ7"
   },
   "source": [
    "# T81-558: Applications of Deep Neural Networks\n",
    "**Module 9: Transfer Learning**\n",
    "* Instructor: [Jeff Heaton](https://sites.wustl.edu/jeffheaton/), McKelvey School of Engineering, [Washington University in St. Louis](https://engineering.wustl.edu/Programs/Pages/default.aspx)\n",
    "* For more information visit the [class website](https://sites.wustl.edu/jeffheaton/t81-558/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4_rQuA1mCfQ7"
   },
   "source": [
    "# Module 9 Material\n",
    "\n",
    "* Part 9.1: Introduction to Keras Transfer Learning [[Video]](https://www.youtube.com/watch?v=AtoeoNwmd7w&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_09_1_keras_transfer.ipynb)\n",
    "* Part 9.2: Keras Transfer Learning for Computer Vision [[Video]](https://www.youtube.com/watch?v=nXcz0V5SfYw&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_09_2_keras_xfer_cv.ipynb)\n",
    "* Part 9.3: Transfer Learning for NLP with Keras [[Video]](https://www.youtube.com/watch?v=PyRsjwLHgAU&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_09_3_transfer_nlp.ipynb)\n",
    "* **Part 9.4: Transfer Learning for Facial Feature Recognition** [[Video]](https://www.youtube.com/watch?v=uUZg33DfCls&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_09_4_facial_points.ipynb)\n",
    "* Part 9.5: Transfer Learning for Style Transfer [[Video]](https://www.youtube.com/watch?v=pLWIaQwkJwU&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_09_5_style_transfer.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JJG34dgaCfQ8"
   },
   "source": [
    "# Google CoLab Instructions\n",
    "\n",
    "The following code ensures that Google CoLab is running the correct version of TensorFlow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "53WPBKDgCfQ8",
    "outputId": "5140ad7e-1266-47e1-f086-92d69ad7a8e5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note: using Google CoLab\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    %tensorflow_version 2.x\n",
    "    COLAB = True\n",
    "    print(\"Note: using Google CoLab\")\n",
    "except:\n",
    "    print(\"Note: not using Google CoLab\")\n",
    "    COLAB = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gHEsbJTZQ7cl"
   },
   "source": [
    "# Part 9.4: Transfer Learning for Facial Points and GANs\n",
    "\n",
    "I designed this notebook to work with Google Colab. You can run it locally; however, you might need to adjust some of the installation scripts contained in this notebook.\n",
    "\n",
    "This part will see how we can use a 3rd party neural network to detect facial features, particularly the location of an individual's eyes. By locating eyes, we can crop portraits consistently. Previously, we saw that GANs could convert a random vector into a realistic-looking portrait. We can also perform the reverse and convert an actual photograph into a numeric vector. If we convert two images into these vectors, we can produce a video that transforms between the two images. \n",
    "\n",
    "NVIDIA trained StyleGAN on portraits consistently cropped with the eyes always in the same location. To successfully convert an image to a vector, we must crop the image similarly to how NVIDIA used cropping. \n",
    "\n",
    "The code presented here allows you to choose a starting and ending image and use StyleGAN2 to produce a \"morph\" video between the two pictures. The preprocessing code will lock in on the exact positioning of each image, so your crop does not have to be perfect. The main point of your crop is for you to remove anything else that might be confused for a face. If multiple faces are detected, you will receive an error.\n",
    "\n",
    "Also, make sure you have selected a GPU Runtime from CoLab. Choose \"Runtime,\" then \"Change Runtime Type,\" and choose GPU for \"Hardware Accelerator.\"\n",
    "\n",
    "These settings allow you to change the high-level configuration. The number of steps determines how long your resulting video is. The video plays at 30 frames a second, so 150 is 5 seconds. You can also specify freeze steps to leave the video unchanged at the beginning and end. You will not likely need to change the network.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "S2vqwfdNcF-n"
   },
   "outputs": [],
   "source": [
    "NETWORK = \"https://nvlabs-fi-cdn.nvidia.com/\"\\\n",
    "  \"stylegan2-ada-pytorch/pretrained/ffhq.pkl\"\n",
    "STEPS = 150\n",
    "FPS = 30\n",
    "FREEZE_STEPS = 30"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Bo1IL05YtbBr"
   },
   "source": [
    "## Upload Starting and Ending Images\n",
    "\n",
    "We will begin by uploading a starting and ending image. The Colab service uploads these images. If you are running this code outside of Colab, these images are likely somewhere on your computer, and you provide the path to these files using the **SOURCE** and **TARGET** variables.\n",
    "\n",
    "Choose your starting image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 73,
     "resources": {
      "http://localhost:8080/nbextensions/google.colab/files.js": {
       "data": "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",
       "headers": [
        [
         "content-type",
         "application/javascript"
        ]
       ],
       "ok": true,
       "status": 200,
       "status_text": ""
      }
     }
    },
    "id": "bYv-Gv3Zl1i8",
    "outputId": "03a88027-1e21-4f1c-9833-faab77be7448"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "     <input type=\"file\" id=\"files-6cb77768-1162-434c-a43f-6d0bfbfc11a5\" name=\"files[]\" multiple disabled\n",
       "        style=\"border:none\" />\n",
       "     <output id=\"result-6cb77768-1162-434c-a43f-6d0bfbfc11a5\">\n",
       "      Upload widget is only available when the cell has been executed in the\n",
       "      current browser session. Please rerun this cell to enable.\n",
       "      </output>\n",
       "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving about-jeff-heaton-2020.jpg to about-jeff-heaton-2020.jpg\n"
     ]
    }
   ],
   "source": [
    "# HIDE OUTPUT\n",
    "import os\n",
    "from google.colab import files\n",
    "\n",
    "uploaded = files.upload()\n",
    "\n",
    "if len(uploaded) != 1:\n",
    "  print(\"Upload exactly 1 file for source.\")\n",
    "else:\n",
    "  for k, v in uploaded.items():\n",
    "    _, ext = os.path.splitext(k)\n",
    "    os.remove(k)\n",
    "    SOURCE_NAME = f\"source{ext}\"\n",
    "    open(SOURCE_NAME, 'wb').write(v)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JYOkqPY_4DJ-"
   },
   "source": [
    "Also, choose your ending image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 73,
     "resources": {
      "http://localhost:8080/nbextensions/google.colab/files.js": {
       "data": "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",
       "headers": [
        [
         "content-type",
         "application/javascript"
        ]
       ],
       "ok": true,
       "status": 200,
       "status_text": ""
      }
     }
    },
    "id": "n5e3J-PNS5WQ",
    "outputId": "169f5b43-19c6-42f6-dfbd-1cc37a121de1"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "     <input type=\"file\" id=\"files-fb8862cf-deb4-4110-9bed-5e04dbaac99f\" name=\"files[]\" multiple disabled\n",
       "        style=\"border:none\" />\n",
       "     <output id=\"result-fb8862cf-deb4-4110-9bed-5e04dbaac99f\">\n",
       "      Upload widget is only available when the cell has been executed in the\n",
       "      current browser session. Please rerun this cell to enable.\n",
       "      </output>\n",
       "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving thor.jpg to thor.jpg\n"
     ]
    }
   ],
   "source": [
    "# HIDE OUTPUT\n",
    "uploaded = files.upload()\n",
    "\n",
    "if len(uploaded) != 1:\n",
    "  print(\"Upload exactly 1 file for target.\")\n",
    "else:\n",
    "  for k, v in uploaded.items():\n",
    "    _, ext = os.path.splitext(k)\n",
    "    os.remove(k)\n",
    "    TARGET_NAME = f\"target{ext}\"\n",
    "    open(TARGET_NAME, 'wb').write(v)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yKzuJGXKQcVK"
   },
   "source": [
    "## Install Software\n",
    "\n",
    "Some software must be installed into Colab, for this notebook to work. We are specifically using these technologies:\n",
    "\n",
    "* [Training Generative Adversarial Networks with Limited Data](https://arxiv.org/abs/2006.06676)\n",
    "Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila\n",
    "* [One-millisecond face alignment with an ensemble of regression trees](https://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Kazemi_One_Millisecond_Face_2014_CVPR_paper.pdf) Vahid Kazemi, Josephine Sullivan\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "HVgGO9LoyUYF",
    "outputId": "78e74d89-17dd-4534-8e00-3399e4436c4b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2022-01-31 02:50:46--  http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2\n",
      "Resolving dlib.net (dlib.net)... 107.180.26.78\n",
      "Connecting to dlib.net (dlib.net)|107.180.26.78|:80... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 5706710 (5.4M)\n",
      "Saving to: ‘shape_predictor_5_face_landmarks.dat.bz2.1’\n",
      "\n",
      "shape_predictor_5_f 100%[===================>]   5.44M  22.4MB/s    in 0.2s    \n",
      "\n",
      "2022-01-31 02:50:46 (22.4 MB/s) - ‘shape_predictor_5_face_landmarks.dat.bz2.1’ saved [5706710/5706710]\n",
      "\n",
      "bzip2: Output file shape_predictor_5_face_landmarks.dat already exists.\n"
     ]
    }
   ],
   "source": [
    "# HIDE OUTPUT\n",
    "!wget http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2\n",
    "!bzip2 -d shape_predictor_5_face_landmarks.dat.bz2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5YSxWFktQiND",
    "outputId": "2ab1c71f-a5f8-4990-9627-77f41991427d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fatal: destination path 'stylegan2-ada-pytorch' already exists and is not an empty directory.\n",
      "Requirement already satisfied: ninja in /usr/local/lib/python3.7/dist-packages (1.10.2.3)\n"
     ]
    }
   ],
   "source": [
    "# HIDE OUTPUT\n",
    "import sys\n",
    "!git clone https://github.com/NVlabs/stylegan2-ada-pytorch.git\n",
    "!pip install ninja\n",
    "sys.path.insert(0, \"/content/stylegan2-ada-pytorch\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Nup7NIthPsyi"
   },
   "source": [
    "## Detecting Facial Features\n",
    "\n",
    "First, I will demonstrate how to detect the facial features we will use for consistent cropping and centering of the images. To accomplish this, we will use the [dlib](http://dlib.net/) package, a neural network library that gives us access to several pretrained models. The [DLIB Face Recognition ResNET Model V1](https://github.com/davisking/dlib-models) is the model we will use; This is a 5-point landmarking model which identifies the corners of the eyes and bottom of the nose. The creators of this network trained it on the dlib 5-point face landmark dataset, which consists of 7198 faces.\n",
    "\n",
    "We begin by initializing dlib and loading the facial features neural network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "_e8cYofTZNF4"
   },
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "import dlib\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "detector = dlib.get_frontal_face_detector()\n",
    "predictor = dlib.shape_predictor('shape_predictor_5_face_landmarks.dat')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MiXAF-Y7U_fa"
   },
   "source": [
    "Let's start by looking at the facial features of the source image. The following code detects the five facial features and displays their coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "PfYwjeleZQDe",
    "outputId": "881d8608-d1d9-4bf0-cf6c-81f65e1ef0d3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1098, 546) (1128, 576)\n",
      "(994, 554) (1024, 584)\n",
      "(731, 556) (761, 586)\n",
      "(833, 556) (863, 586)\n",
      "(925, 729) (955, 759)\n"
     ]
    }
   ],
   "source": [
    "img = cv2.imread(SOURCE_NAME)\n",
    "if img is None:\n",
    "    raise ValueError(\"Source image not found\")\n",
    "\n",
    "gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "rects = detector(gray, 0)\n",
    "\n",
    "if len(rects) == 0:\n",
    "  raise ValueError(\"No faces detected\")\n",
    "elif len(rects) > 1:\n",
    "  raise ValueError(\"Multiple faces detected\")\n",
    "\n",
    "shape = predictor(gray, rects[0])\n",
    "\n",
    "w = img.shape[0]//50\n",
    "\n",
    "for i in range(0, 5):\n",
    "  pt1 = (shape.part(i).x, shape.part(i).y)\n",
    "  pt2 = (shape.part(i).x+w, shape.part(i).y+w)\n",
    "  cv2.rectangle(img,pt1,pt2,(0,255,255),4)\n",
    "  print(pt1,pt2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "l8a4lUalVj1-"
   },
   "source": [
    "We can easily plot these features onto the source image. You can see the corners of the eyes and the base of the nose."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 281
    },
    "id": "Sj9lIQTlZUo-",
    "outputId": "936b8306-f2d1-4419-ff70-08c3923dccd5"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
    "plt.imshow(img)\n",
    "plt.title('source')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UPjN2RvZOaMv"
   },
   "source": [
    "## Preprocess Images for Best StyleGAN Results\n",
    "\n",
    "Using dlib, we will center and crop the source and target image, using the eye positions as reference. I created two functions to accomplish this task. The first calls dlib and find the locations of the person's eyes. The second uses the eye locations to center the image around the eyes. We do not exactly center; we are offsetting slightly to center, similar to the original StyleGAN training set. I determined this offset by detecting the eyes of a generated StyleGAN face. The distance between the eyes gives us a means of telling how big the face is, which we use to scale the images consistently.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "OuhPPa54912r"
   },
   "outputs": [],
   "source": [
    "def find_eyes(img):\n",
    "  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "  rects = detector(gray, 0)\n",
    "  \n",
    "  if len(rects) == 0:\n",
    "    raise ValueError(\"No faces detected\")\n",
    "  elif len(rects) > 1:\n",
    "    raise ValueError(\"Multiple faces detected\")\n",
    "\n",
    "  shape = predictor(gray, rects[0])\n",
    "  features = []\n",
    "\n",
    "  for i in range(0, 5):\n",
    "    features.append((i, (shape.part(i).x, shape.part(i).y)))\n",
    "\n",
    "  return (int(features[3][1][0] + features[2][1][0]) // 2, \\\n",
    "    int(features[3][1][1] + features[2][1][1]) // 2), \\\n",
    "    (int(features[1][1][0] + features[0][1][0]) // 2, \\\n",
    "    int(features[1][1][1] + features[0][1][1]) // 2)\n",
    "\n",
    "def crop_stylegan(img):\n",
    "  left_eye, right_eye = find_eyes(img)\n",
    "  # Calculate the size of the face\n",
    "  d = abs(right_eye[0] - left_eye[0])\n",
    "  z = 255/d\n",
    "  # Consider the aspect ratio\n",
    "  ar = img.shape[0]/img.shape[1]\n",
    "  w = img.shape[1] * z\n",
    "  img2 = cv2.resize(img, (int(w), int(w*ar)))\n",
    "  bordersize = 1024\n",
    "  img3 = cv2.copyMakeBorder(\n",
    "      img2,\n",
    "      top=bordersize,\n",
    "      bottom=bordersize,\n",
    "      left=bordersize,\n",
    "      right=bordersize,\n",
    "      borderType=cv2.BORDER_REPLICATE)\n",
    "\n",
    "  left_eye2, right_eye2 = find_eyes(img3)\n",
    "\n",
    "  # Adjust to the offset used by StyleGAN2\n",
    "  crop1 = left_eye2[0] - 385 \n",
    "  crop0 = left_eye2[1] - 490\n",
    "  return img3[crop0:crop0+1024,crop1:crop1+1024]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "l93W0Dqt9HKt"
   },
   "source": [
    "The following code will preprocess and crop your images.  If you receive an error indicating multiple faces were found, try to crop your image better or obscure the background.  If the program does not see a face, then attempt to obtain a clearer and more high-resolution image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 562
    },
    "id": "Kfm-t89i7OIw",
    "outputId": "e99b79f3-13e3-43f5-8be2-1d8a414662b0"
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQ8AAAEICAYAAABBKnGGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy9a6xtWXbf9RtjrrX3edxH1a1H17Orqt0dP9pP7NiWQhABITAIWUIivBRhQDJ88IdIEYoTIgQRD/MFxRJSwBIIogCOJYICyCIikZASEkKIldgJHdttx+V+P6v63nvO2XutOcfgwxhzrXVuVbe7brfL19GZ3bvOufvsvfbac445xn/8x2OKu3MzbsbNuBnvdejv9A3cjJtxM353jhvlcTNuxs14rHGjPG7GzbgZjzVulMfNuBk347HGjfK4GTfjZjzWuFEeN+Nm3IzHGjfK42bcjJvxWONGedyMm3EzHmvcKI+b8b4MESm/0/dwM76540Z53AwAROSPisinROSBiPyyiPyTIrIXkT8lIp/Ox58SkX2+/sdE5K8+cg0XkQ/n7/+tiPxpEfl5EbkA/oCIvCoif15EviAiXxKR/2Lz3n9TRD4mIm+JyF8Ukdfe1wm4Ge953CiPm4GIfCvwE8DvdffbwD8N/Abw7wE/DHwv8D3ADwJ/4j1c+l8F/mPgNvDXgf8NeBN4HXgZ+Nn8/B8F/jjwLwDPAX8F+B+/sW91M367x43yuBkADdgD3yEio7v/hrv/GvCvAX/S3T/v7l8A/kPgD72H6/4Fd/+/3N2A7wZeAv5dd79w94O7d+Ty7wD/qbt/zN0r8J8A33uDPp7scaM8bgbu/nHgDwP/AfB5EflZEXmJ2Oxvbl76Zj739Y5PbH5/FXgzlcOj4zXgp0XkbRF5G/gyIAQ6uRlP6LhRHjcDAHf/H9z9HyU2sgP/GfDp/HcfH8znAC6As/4HEXnh3S67+f0TwAdFZHiX130C+Lfd/anN49Td/9rjf6Ob8ds9bpTHzUBEvlVE/okkQw/AFWAE7/AnROQ5EXkW+PeBP5tv+zvAR0Xke0XkhEAtX2v8P8BngJ8SkXMRORGR35d/+y+BPyYiH837uSsi/+I38zvejG/+uFEeNwOC7/gp4IvAZ4HngT8G/EfA/wv8IvBLwC/kc7j7rwB/EvhLwK8Cf/UdV90Md2/APw98GPhN4JPAv5R/+58JpPOzInIf+LvAj3wzv+DN+OYPuWkGdDNuxs14nHGDPG7GzbgZjzXed+UhIv9MJiF9XER+8v3+/JtxM27GN2e8r25Lpij/CvBPET7v3wT+FXf//963m7gZN+NmfFPG+408fhD4uLv/urtPRIbhj77P93AzbsbN+CaMd4u5/3aOl7meOPRJ4Ie2LxCRHwd+HEBFvv/8bIdqQVVREbRo/q6ICAhI/AcczA0zx8xo1rBmtNrw1sCMUYXT3ciuKKqCiCIsb6eZMzdjqk6thrvQPFIwXcBFEY33qgpDUXaDMKjkN3DcHXfD8mc1Z67G3AwRQUXi3gERKNK1uCACqkIp8TpEiL/GXTpg5jRzajOaOY6Dg4hzulNOx0LRuJYAAS7jvpo7x2pcHCtmvtzHNiXDHcw95tHj3/2vkvc+FuVsXzgZh+X7iwjS5yAv6cQ1zGJuO9D1nM+Yb5jNQXI9REEVJL7v9vP7hcVjNjxv0H2d99YM91x7a7g13B0eRdkScrQb43sMqsv382Ve4h6aO1PzfCaWRYRYS5WUx/hrX1/J55YZdk/5NFThdKfsB2VImS6lIGUASZvuhpthreLWmGrl6jBzOFbct2vXrx2ya2a53pt704KWQhHN52S5/09+7otfdPfneI/j/VYev+Vw958Bfgbg/HTnP/Rdb3Dr1i1OTk7Z7fbcunXK+fkZJ/tThmHICRdUFTNjmo5cXlxxdXXk/sOH3L94yMVbX2H68n2GwxXf8uw53/f6B3j+9hknw8h+2DHogKpQ3XhwUfnkly/5jc9e8LnPH7mclPtmPBBhKoU6njKcnXF6OnJ6Vnj29gmvP3fCndOCiGNesenIcZ64mo4cpyMPDjOfevvAF+5fMRTlfLdj3JdQJBhPnSgnhBIspXB6uuP2+cB+HJBhT2PAZQQGmsPlsfGVi5m3Hh55eJhDQTXjZGh896unfPSlO9w+hUEFzd1XrTFb43Ka+NUvXvA3Pv4lLi4q+7HEPlUAAYd5DgG9ODYuJ+NQC80tFWZhHHe8fO+M7/vg03z7K0/zyjM7nj7fsRuEArFxrSEUKs7Dg/H2g8r9BzOHqeE4Oig+DFxW4ZMXxucPFXdl3J9S9meU/TnsRpoUjrNTDTDDmyFmaGtoa7TjAZ8r1irTdODhxQUXl5dMh0suLx5w//5XOB4eYvWAzqFQHFAd0PGM05NTPvTCM3zkxae4dx4ypmXAy0ATDeMB3J8rH//iFU5hVEHFGEZhf7Lj5GTH6U45GXfsysB+v2e/23My7mLOiiIOdZq4PF5wnGb2+8pHP3jGd7z0FM/dPuHs1hlnt59iOH8KxhNcHKkT9eIBV29/mcODt/j0l7/ML/7a5/j4r32B43GilN0i9+7O5XTk8/cvubi6xNoMCGV3wv70FuX0nLOz25yfnHG6P2E/7jjZKScnyh/5qf/qzXfdjL/FeL+Vx6eINOU+XsnnvurYaldZLDGL5t3+fXmdKu4sllDTwpye7Hj26VPu3Rq5fTYwlsJuUEYtqAiVQjNhNwqKIx5W/frnpIWjW/XYuNUUJKyemTMb1BbopVXDDNxl+R4dDUgiFnNDPD6nNmOaw4qKGU0dw0DCih+qcWwwNagumHWk0HCH1hpzdUyFIoKbhfJoldoaU6tUN1zjPlQVLQBKq22d5/zKHU3IYl090Z6ExTPDLZBKf62ZISjmUGfjOFWOtTFVw3DUnUEG9mWHlhmRhqgyaKFoYSgFSkEA01hHo4AtuAbfwphci+aGEUjBFqThgeLynjsC6ShQNSx/H57rHjKmqHTZU5qBmKMpVzaDDdAGobngErIX9+Y4QktZms1ohDIyNBTxMDKOA2UYUSmAgocsrfezookQbJbP6MgLnHEonIyF1gbq1HARhg2yIeegmlOaUz1Q7OOO91t5/E3gIyLyBqE0/mWi8vJrDpGwiAIBVz0Wz4lNVSix8XwDFdVQEUr+b9DC2V64e+uE09Md+52yGwZ2pTCWIaCcObvaKIOtuJqAdoMoUzoXTl9YpTlMzZnn2ITNhGZCbVCrM88eLpAZLo7Khmby2BTNlcka4oZKQwyGOZQCPoEWmgA0zIXD1KitUd1oOQdGo3m4M8fZ2A3gxfN9ztwax7lxcazUWRALR60rRln8G18Ub3fNRA0xyec0obrFBpNQJOE6CS4Jtc1xnZmscJwbx+bMLRCQACYjzRUE1Bu4oVqQAruiGyQkNDFMwi3znP1CwCUXCXcSoaK4a7gxhAIJd0WBQgoNeCiwQhgaEUc8FGlzQwmkoKloFKEg8T/Je8trGOAimIDh4d7iIE7DKTjFpE8tNCdUR2MUQZRwJ3TjrkjIOUSab0WYrWGWM+1hRIZ+TcK5Upz9IMyjIChgDCOBCItT3Ba3vpozmzO1r2PXfpXxvioPd68i8hPAXwQK8N+4+9/7aq/f+oqrP036xuvf46kU7kQZRcNiFJH4qcrpvnB2sme/G9jtwi0Yy8CoJfSEOcMQfMY1H3uxwLHh3H3xGZs5x6lxHLrbYrTmTLNzmJ3DDMcaiy14CuuKQEhuAQM3o4gw50aLYtQG2qhiqEBLRDPVRm2+IBozaOIca+U4NU7HQjNLpGDU6kwVLg+Ni0OlNoOcV80N5ImEVsvZFUjMTV+LIs5QYl7TzQ/koWHJgjOBWo2r2TmkkNZUrKK+bIJAQvEGKaxrWBRKCQVr8XoRwVRQS1noim8jMQvWyI0SioVl/g3Hk2Pq69AVTXPJTRuKostdtRbvUWFwRd2SY1oRqZL3vZHHjpDYbPIkggLxdDQrXSk0SEXaX9cN5lyhNiil0ByqxQYSSYSkcde7QTkxpeSslEHYj0oZCqikC2t4a2iDsb0TuX+9433nPNz954Gf/7peLJufi6CvCkI0H8iqPAi/Wz0gu6gj6hR1RlVGFcYiDIOggYwpGtar4YjESsv2HjYKxAmFJLmqbk5rcGyGqNNao1ZjqsZVNa5m41hJcjI35bX18iD4OhkrQnVCkI0g/VqlSVinZqE4pmY0A0vL0QyqrIrl8mCUEmBfJAjb49w4VLg4NubaEgWn8NE3QyA3M1vcIFLBkK8ZVBgUBo2569/DLEllj/uZqnM5Ow+mxtXUmBtU09yUBapwcOOyOm5B7nX2WjpZal2JgbXuLi2ylPMp1/69kIkioRRSaYh7oAS33KyxoGbGVBvH2fDiuMY+MxHEA01Us5Cza8vXjZgwqDKIXvv74io86hmkIjKLtTVrtNYobcbqjOgY928GLWRsqs48G4hinq4HjnYXPV3eonBSYDAHFcog7EZFBqFpoiM33HI96u8i5fFeR7dE4WSu/IWqBnMsGYUhFsvz9SXhdVENv3+j6V1AtCsAcA0/2THMk5mXDpDXKYpN1v1HwgdGmQzG6qg61mCuEUGYZpiqMbfYAJJwOC+/QPCWfryIYa7BmnehrzDTcKkMKlTLa9bkWlrDaeHipJJ4OM9ACV8Xo3llbpW5wdUU7otVR1WuKTJZIgUasNdt+c4iofzC15fkJkDTbTGL93nC4mZQK1wdGvcvJh4enHkKZediYEKbnItUsEG6hPLvUZZQAL64DohjXbnnnrzu+3MtGmXJXfRhykKY2sZ9nKpxnBonpSGl4NLCjZEh3BFvzOaoGKiiHoJTerSlczgKY9GUOSVnMdBcRsXiniOCd2yNaa7Mc2NfGrVUhqFSdAYteG3UWmltZp4bh2Ojzp7IOAxeuE+h2HALxVRgMA1Dp6FQRFMjIsweSrmZUdvjZ2s84cpjI9kZvStJAmoqhe4GFAmLVpL86o+YrtDK1iKU1dIn7svZrAXMbkazGsIgOdeBTxcLJ+lri6aXKYWWJJS64y0iA9PcmGpYePMI+YqvocwFbOdGqeYIlteFqVUExb1QxRC1hJzxHcK1aTTvYbnYJHN1Hh5mcGMsQfyaxb0ca+XBYWauLRDaEvLWtMSSljvuS7QgYoGiOyhId0akREhZdOHxmkHnTCzdq+OxcXVofOWycTy2QEoqWKlUGZgazA46yqIAOvLI2V8JTvd0TLw7IOCyEKM9XOl012t9gGAe7gkE9dC5xqk6V7Ox04proaHoWHCMphKbDKGk4urbraSy2A0acx2capL0m5Ctyope89fanKsp0ODcgsOSWpF5xqUgWrA6c5zicZgrD6+OHI81FUKGlYmwdcxBpAegipYShnUYYh+o4hIcnaTyM/PNt3nv4wlXHlufPNWAaBJMMSGw+p4devfnOmzsZGBtRp1namr0PvEiYe1rDbdjibD0z7XNZ+jK0PfPd3dqkllWjalVptaWzd0jK3mDC4xduAbvnIhSDbQFdxIQyfESLow4qahC2bTMZyERU/OA31dHcGthBSUiPcfaOE6Nh8eZeZ7TPZElemJuuG2iL6LIQgznBtxs6tW18Iz0dFegLfkM1SqzGVeT8eCqcnmo4dogyDjgQ8vIg+CtbSIU64jcnkJrtkQLttPZlV2gj1Cwvsw5CycUvJDgrsSWiaiGNWGejeNkHNWR4swYxSIaZRoRozlUAoMk3+UwCBQ8Q7cbWVR5RG5ziCzK0DO/5TAbh3nmZJgC9dRK0Qbi1OnI1eHAw8PEw8Mc7ubcGCRcpLJxmzxR4urqy8IJLUhlIcQ7CSOPzPZ7G0+48ogRBGUk0SwRgJwU+ibOTd6FOpX8qlBEmOvMca7MtXKcQNglotEMcRqttST9bL2WdvepI7+4Xk/ics/QG7ExWiaodURj3Zr377P8XAUxSL1g/ZutFld6hIAI8TXviVWNZrG5LZOJIpHJOM4CLkzSw83GVCvHqXJIl8cAMYJUta5gN5Z6o4SXBKvtRkgLbwmBLSaB4D7CnQquwNNdMi6P4V6JCINHcpwUvXbdhcdgnfMiEmHlXF8HSA5kO5tcuz3LMGT4u+5dGvT6vQPmwlyD5JZiDBrhVVePSE84huE+FRhEcJNEwo4qi0xCuNbvmL/8bt21AqE1OBwrl4eJnRY8ea0x7/l4PHB1OPLwauLBoXI1Gw2laGFXCoMqLo43UAsiGCGUZLp2cU8dpXRH6vreetzxhCuPvuDBZhdRisoSd5ckTSmZgZnSpZsFWzS/R+7FxbFxdayc7pShpa+IrBbLFDcy/BkCFKG+QAmIEUi9K40QNCzDat0lSmtsCaXNAzr0BXYhLbvENaVldCWv27M/c3OiFUcD5lujWsNoGUYI9NGac5gr05BZhWllzBpTixyLq9m5mJy5BcauLZRLV7iehJpZW7JMkdX1i1UJJFQrCwqq+bqVcyByXXCOLdy3yIFJS5hzWrTQRBYlskWZJbdZSYXdOhuppBICUkF2q75VPoGAJJCNBwLp4XdHsS5e1nNjGlSjCYg5Vhqu+RZNFyG5BtcgVi2jwNsomku8MrBkIJ0alG1mroa7NdfG1Ww8vGwUbZhU9sxYi2sdjgcuLmfevpi4f2wcWyg6VdgPoVRb7g5VT6MT99AAk0SDaKKTTRQx3cu2QZfvdTzhyiMEpLsI17gM+SrhuhSebdJPV0K1GtPUqHOkrLdSM/E7t00n2NLS6VAyHyLZ2oxKXNfVskRRHFs2/hKytPTOEx0sSo2u9ROKe/++a+Sop1u7WmwCa9REC41IHJIFgoarcpyFi6KYt+W+Agk4V8fG5bFGxqaDWEO9RKQjBT/cN2NqoRCad+flujLuadadf5mq5QaOtPfWjLnCYTKmyWktk8nShXBbIzydpI11DcJxKAXVguMU7/kdHuiTUFhLCvkGcfTRSxT6Y5nLPleL/Y8NNbdIP/fquFi4srlGS1RPV7m6tk6b+WE7V8saX3fxIiwc32GqxmGaKVeKozQf2bUBBK6OlYdXM/ePzsUx5rlZrOs4Zv6SONpIlDcmj6PU1vkprt/XQitt+JjHHL8LlMdCea48xvrHFS6av8PqsPndiQ3dqi3uSa2aOjkmsLYUsu4OFUeGMC8RKYlQWVIo/RZI/2aF/Sbro/vjnXBNV6dzMV2oHx09guASEZkQOqN5II9mtorrQiQGEXc5Ga3160dYrrbGYa5ryBSnDIprr6dI9NUiTFzNqS3cMfc1z2KZW2ID1mYcawviVMA9wo7NnMMUyuM4t3VuvSOCRF2scwEEX6CaNUxp6z3yX1J/YxbuXmPVG/YuG6W7fpunuL7Ju2yECzObIS2UtaqvygOnJMG8LHJnQBdW9prUXvu5zfewVILVndmE2jxcpsko0sBnWisgcJhC2T88NC5no9aGEmUCMgTvgYfbZFIClTZjnvs6rbKXXG+4Mym3sviAjzeeeOXR16GHD3u0wzIUS0YIFv258Z9FIk6fAYGw3F6ZvVKrUEuhZAgSFDfFvIaCKALFUSPJtU7CCZigPTtSIoXZF2KO9XX0SEh6VIsLdp0WDPemLSnUXd5rujXeMkXbwVvUd7g51SNxTCzuwzzyJVqrTDYucm5u1BokbuvoRwS3ATFNgk/7V4u5oCwkm7oHw78oWqU6TIk8am1MEi6gJTE9t8Zhco7HyjSHS9V5B8+ZqQbFOm8lSBGsRG5CKSAFvDpjhq/VoRVBWgh9bRHydTSI0ZYX7iPlQpN3WuLksGQpK2S0Qpgzbj4OURYgMmDJpSmEEKlG1MUbo2RRo9m19dwq10WA8/MKgrhmflBhbko1Za7CoE7RhmgDLRxn4dgiqSsUckNdGHTAtQXnAah38ttwK7FHXOOLEQf1GUbFsazXCWM8Ru3TY44nWnl0wmetBZHk7VYyanlh/nw3ELZAVoeW9SZTNVQr4ho1ExKh3JZJSZ2QvR7JWdHDQqWQ8qirQdq6IOs9dJ6ju0mhXEKxZG2IyOLL92rc8NsaVmRzPV8u2h0pNwfR4BUEmlq6LJ7pyAHNlxClKlJGREvUYxgRXSA5AqTjbiIUHspLtWdDeqbfG9Ooi0J0N6YWSuXqUBfkMVWwzCnQAjoG32I1OKRRhiU/YhCNCtdSYhNbptl7R50WCa/u19yS9Wf/PbigrsS/mpB5upgdT5gZeo3cjOcoJfM6gOW/K6rYuihL9qlcBz+d1621cZiFw1w4VmUoMLhQepZrr42yMDxuIFJwaoTz8xHXjM/RTMBbP042srbK4Pbf775jvr7xRCuPdawLsf2ua2HUquEfRa/LXEn3tYV5bkxzkHV4Y/BKhExjwcx99cMfCbWtKckrL0ESaQssTHekf/ijWaVLYV2+vic1qWQSVW6C1l9UGq4FdcPamhHaBZ90Ydyh5nPV20IgRs1LRmoiz5oy7CnDCGUIYdPkOyxfI4qk799hb7QKULQECWsGcxWOc0SJevbibKFYrqYIgV4dG1fHlnx2pHhLi+9dzBgzGqCqjKUwlqhFkqxIVSxS0leWlNo9hs5V5SOiZY3V+rfl8W4KZHVpt9xIn+NElYta6Z6PLzIXuRJs5GIjm48YkWsciRnHuXI5KZezUIaR0iyRCdAii7haDzcnke9ki4Ee3wv5XonulVeDKDfQLJveKrXVOL5jSr7u8WQrDw9tu6EJlnqKQv6eQhTlF5uNuxmZ2gVk8tLsHKfIGPSh4TagJfiE42wc5znSwxPCd4I8rIYhEn5n/NspBKy2TNKJYqmsdKWnonW2PqMbnaRMEi+EsEV245L7EdWVLkZxp0lPtU4Y3qGOaEZdUgFaljHQokjNjZZ5IC6K6o6iQ8yKhQULYYLSIgdCkrS0NoM7424EYs5GUbwF3HKcQ51wG/M7R4LbVOco55/jMU0RApeioeCasDfAjZHI5ygilMy1iITITEvPsKh6fK+WPoQvnFFmS6bimlu4Tt4cdcG8S8BWCXRkkhwMDWdIwjHes3JVoSAiapYkq0d4dBAiYzYNxVaByErp5PMpCR4RkNaEw+xcHiuDHkPWxxrZrybMSTy3zPupzSlNwsA0FresI6u5ZsTFWy/eiW+8kBxKf0egaVnm43HGk608ZIVdXXnEYqQvew1AbsCabJ5f/IoQkuNsXFzVqNzs3g4gLQizq6NxOEZ0YOUputAJvXhhKRzLz7DuDqSK6P+2pclNt1pxf/E+XzgJtwjltVZRLQsMlkyF73cQKCKyVqNGI6HnspECYfSkoXB/MidEIoTbPeFBYFciTBrFqMIw7iCb6BgwFGEQ587ZyNXVYfksEzjWGuioGZdtxlBkExZ+eDXTmlLnSmSkEuFQGjIaxZxBeqVuL2jMTOIS99rU0RJoSltySPiSX7LwlTnfzZxmskS7cN1wTtf9B3db16AZVmLdiwpSEjmEf7Q0MxIJEhsP+avOQqz26/cksZUg73t3rUpuKbW1hUweijEMTplCvoRwrWu60h01hvsJNBg9FGp3F+dm6dltUNISDepKbaMw+p56zPFkK4/t2PAfW/gXSlWuycU7Qmi5Ed2y1uKqsRsy7m6ODSGwc3MOVzAfhTp3ofR33EMf2+xK1Qh5htshSVzGm5aMR9kKFitygCWFHclmNb17WH9juj5bmA6PoizPzRB9I8xIGBtcj/e6C1V2Q9Sm3D7doUVDESC4N1qJTmE0sNo4O9nxwp0zvlArh7nlrUdFrFvlgy88zWfffpuHVxOTCXMTHl42Lo+x6dScIiWybucWhYiZ4LaItMg1zqMs3dN624CNa+B9XsOE9LluWWXcqtOqp4tnK0f1qEvbLTPhFlhyC83CmGiBXpbbc1e0hCYS6WHs6ONhvunstXoNWW/Vq8JlkVcRwcQyxCocZxhnKKOjxSma+TMekRRLkro1IkfH4nN7gd/WmCzz2rm6/H1RZl/FxX+v48lXHgs6SGgtmq7MJmlJNouyfW+3Kt1rtcjoe3BZ2euAewETbGhoCeVxNRlzlQzPrpZdlgnvyMLAFC2xKNZ9ZTyzS20RZpfgAzoKWis6t/46K5eRGZHuIOrd6e1O/uY9FujLV+fI00p2qN3MM22bRVntBuVkiL4UZpVx3LHTiJ5Ub4wqnA2FY4tSgJOi1OnI2W7kZH9Cc2NXdux05DA1PvP2Q9Ad1abI1ZhnaiX6mtTgDabjkWPtXE+upUegvBfoifSUfY3sUw0F2B0O6/47oZwtr9+MzIOJ0GeH+l9rcywrGgKS6KSnsTuSbRIkE8u2kTTXyAIWX3mknkk8ZgZ0Kb2Yc5XNJQFuUS6SaySRql6NsUFp6V6nIus1OK2XJTSPAr8S2Lu1lPAiqLHwG5GevCq0yPswMnaEbBoOPc544pWHdwKp44i0On08SlJt5WXhHPJ5d2eqUWNxOTRUDGmNNlZ0CEh4rJHf0AnQXvtSouEH1oVJ8qdF3oU4NKvUVmmZAdqTgSKCEfxI5H0a3tOkPSMlrBCyCzKAW4QNu1vjaV2C4wGSIxHWTRCR5exXJc6UscZC8grFOR0Hxt1IKVGQN2phLGA0xl1BKByOwuEAw1DYD3A2jjjKl6+m5FAaKjs++9YleDStKWrcOdlz/7IyiHAxzczzEc3eHJ07VgddWvqB9sIyiU5iKiBujB2t5fcz0aUPZygRXbNcPanR3stjQ6S/u3D5xiysCiJ1bzybrzGXQEO+htI95dNcqISRQlirlbPVg27l1UNLekcAHg2Iqkd2cric2Te3xbWVUAqRJr8+cEMXdwqkxXcQjertpUqP7m0n77bwMP4N+S2/C5THdfOxpAFfi3zk37q7ktb5WmFSd2EbHA/GlcKIMlgoAWlOQ6lNs6VekGw9Ae2aEKZQRmNkwVIRmGv4pd7TttMqSJCp2YuFaFQTOSgL5Mx+EeHErnkrC8fggSAyq4EhUk+CC0gjl3eSghL8wLgbKKbUGpv5/GTH2X6k+Iy6cz7seOp0xx7j2Vun3No9xa1ROClR9FUCu1NKRGKujhP3D5UHs+PDiA6FBxcV04EHVxPeZiYHb1C0UP2Y3yP4gqg2hVGhYAwazZgKwn4Y2A2KigfyIPiF4k4vLDIxNN2za3Livrho70wW3Bqd7syufT7W8OWqzCVR3Jb3YJfrVnEAACAASURBVEGMXTGtn2Eu2WJQFq6hyyQbl6a7DZ7Eeu8VUqx3YMsGyT3K0zf/4opHK8SWoEHzOxRlkZut67I8JDN5Wd2++P8/xMpjWVdSW3L99/53ZY17rxZ8TYGGnoUpWBWmCQ7qDL3V4BhOSrVuHdOf7gIinUCNz2tmDDJiHs13IDZyTbZ/tnhElmgLrFE6/7HWnbhvXIrufmX/B+ml/xt/v/WWfQhj9vfAI8w7FEHNssMUkVSEcn6yY5SRp/bK83fPeeHOLZ453XG+E+6e77lzsmNP49Y+2jIWEbxV3CrDMKBFs70g1GkPtCD8yikm8OBqx9SEL1wceft4ZKrC4MaxOrDj6ZNTvnJhfOH+gWYwlqhbGVLpjSWUx8luF02GhOxGHyn5ntWB3iMwskGc293i6/r0zR6/+SMvoPtI72J5163nuem7EulIxqxHw1bCtjnZxKnXB+Z7t64pmSmcyXqS3dWqKKPbxvXd3EYOg+V+XYJHMSEyq5O7WVoAmKy9bbSjtDRA273Uv9tjjideeSCec9alJEKlgqMSfRsFyV6aYd36Y7EQWUfRG9Gy5CTEZh/r6o+KKbQs1acRPTsE14b4yMK8CUSAL4Xcu0CRORWy+OJh/GKDN3qmZaaXO9lQ1xf3Q8RSEabrIhlWzmfCKkf7/ki2dMTm2IQlpLkI3Dk94e7Zjg8+d4fXnrnLi7f2PLUvnO2UfVGKOruxRMQDYzeWpYOYDIpYiEdUjQ6YOidDWaz8MMQXuDPswOGNuzuO9RYXs/H2vRO+cpx5axI+d1H5tU+/TTM4TMrRGoM4Y5kRHVAzdhCJWRY9WcbMP6kWbqtYrkkiEEmSxFUiC7QbjnQrrxsMtqCji1WE+1nR6+KOSKyOSKzjpitMXKiv6ZKDEWtgQA2eOdyPpBciHX0tkvRcs+ZCbULTsri4zbPYTVmMobnTNEL14Y1o5LwQLQPEJbgxccSjUFQs9kxJNy9a1m6TFkgFd73K9r2MJ155vANUyfUs03gqF//dtGgSWWFFQjv31wkLB7l8UkcqCzu+sOSy9sPsV8jPtSVJK92QnnBEfnbvU9YhtWVHLPfMmM6IjXRSq8PduKEhfX6zilijEC5II3p6uvdOavDU2Z67+4Hnzvd85OXneeWpc+6dFc53A7vs0RHR38bpbhdJcC34n0EkhTb5mOxx2BVr6fNtjqtFGNk9GhdL8D+70blVnGd3I8dZOaJcGXz3M3t++QsP+AdfOvLJB42Z4F4Gjbkq2SldiWbTJXuslI0boNJLFAN2uncyeF33BRGwuizvNjrYW6FtL1PYyFRHGxuSc+sW9fqpR/OKev1Kl5X1M/N/vV2Ar9/BTJfcHcs2CdcS1rqrnnxK74aHEwpAWqyTyaJgFplOnffoXnp8zBHjiVce2y/oGyXAI88D62bfcCGRnhV/e4cs5WuuHSC1QF6uuUvx3mASVDbC2xnA5T48rxORoer9CAALBGMaIbVF4Fb/vd9fN5KaRWKCoVIiu9MCDZkZmh3X9+PIvVu3ef72KR9+/i6vP3OL505PuXUysFNjQBiGbInrThkkszjTag3RJUusxyeJ/iBi144lCF6GbP+YEqmB4HAPxQMwKMUHxnHHLZxmM/d2ymv37vDlh8ZvfmXmzbcm3rxoHMQzOlFo1th5kMpWK6K6KI+u2mdvG15nXcNHZWHZ0Lme70wcZDEMj/7h0bKHWGNdrtPlbDE718KfeWMq2MpXLpt/uc+NK9Tfs+VqHr3nbjBd1tR07yURPTs5q6xlxVuL5ujPOev3e4dhfo/jiVcePWwZ6+HZM/OREJMYvVGGukd3axK0uq+WYNMQxlm1d+/X4ICpIQV6yaYUjWw+ojW+k8RYlmyPJdK43aKUzHAGNHnPTNTKtOwF3ibxSdZeNHoD5ERGLpgrUrIPK5rFV7okKGEVEeOZu2e8/uxTfPuLT/PGvXPunu8ZaAwaZ3hYhd1ujAgG/XS6lpyCMWgwr6pECjyxMU1Ay7iB9L4kOPWDpLpF7N2+elwpQukDJFSvVREdOFXh9jDz0m3hu54b+fSl8Ov3G59z5WowjvMRLaE4fCy4l3WJ001cCj8kYXonV53sF/yIklhyH+ya5eh9b3vWb7ccQrhJGcwMGSmSpGY24EnX9zo5u0KTjPIucmXmWMkNz+q2xHtXXm1RZMvm7sih36t0Zjw4OOlC09FRohVrSx+WQudIorUhSMqjx5Eacn2+3st44pXHmqPQ3YyOJHo36yXhdhGErUZ9t6lZLJasP68hHK4jikcL3JbrbtBKWIX4y3pPLG4MYrgGYrAGTqCGgLB1rafJb6JIsvzG3Vun7IaBuc4cjkcqztnZCa89e5tve+E5PvTMU9w+LZxo9NLEo6S7iLLbRfe1oWRn+YTgvbp8yT/QtFhZlg5BVj5al7GNIkSilzMMQyjEbEC0RAbE8doQJHgVUcaTExy4fVK5dzrzxl3hrRk+Mzm/8mDisgpTPaJ1YFDCT39HE5u+Wf3aenlfmI6ENg5pplNt1rFHQDZp2p3A3jqyHbnIqma6IXjX0V0E3baq9Gww5ev1lv+u8rTKTFdmGxdaMtEtZa6Usrhd5o3W8v5TczWLupZqHmkGm74dvaYlOOPHxx9PvPLYgqul6McNsZr1D7qctaGeyysbF4a+SD3JjOX3a5A1fdtHsxnXDbNC1L7kvQdpPGfrvT5y7Q4/IyQbHbHEW+RvsHbtkrRqkqyrDgNtmnn48JKyE4o07uwLr9y7x4eevcOrz9zm9knhbB9nqYwigcwcIIrMiigqcQxDWe6q0DNPIiJgy0ZZFKuvjW/8kd875A8kEnMX87lu4K6bSxkoxbHW0hWLOasU9ntlGBt398Kzx0te2RU+64VPzG9x8AbjCdHBoiAlraZvlHveB77hmbZ/7wu19Rg2m75X3j7q0iwagK6DuisQq9wT8Lajo5CUrmvys63OXhBOytm17yGrtHfltl5jjQxtI00uEi0bPNFvQtjm4ZIW17RBBlIyzyiTLXXzgY8xnmjlEesWSyZdIaRVEfGwltn6PyBsRNkT0RKZl9AbCS9WseS1RaCf/5KLp57xcO1KKIvet4hyI4mC58mAq1CALffWLaVnRWxrwYBLtijs1iLcGcdaTSJM8HnGvMEMw27H87dO+d5Xn+ON557jzskOpTIMcXrajsIwlMX/LUNhLOOCDjSzDQMhrA1hgEwqCldPS4lCPB3AemFdZDSqSva5UHpDcKQL+sotRSUuObdLomXMWG6KoiHGSizWU6fCraHxrF3xijU+MU985vKMz01QZeDW7acxokNaBx2eJMuW57jWCHijMLqrwVbJc33TLzRJ39Te109ozRnKinq2fWmvcxWrm7FGA6NzeW8opBuFsjhOqevWIkVdUvg7ou2Ecf8MIGUna6g8ZLHX4RTpMtV5wr4xtqjmt9qFX3080cpjVe85MbBEJxYj36uSF8Sw2IzrF8kiqO6LBpyMnhHkCeIA5OZa+zZszOg1cAlEKdjaSzKheRiJ68qDbNbTWvSmiMpK6bRHnsFBhJUl3RmvlFF59ulbfPS1l3j9udu8dPsWY1HG4iiFosKow5IAVJIILUPJ+SkoJa1UWP6SHTt6M69+nq2bYSLRWV664k60QInjMOniHv51ZFF6HEBNVyJRQhDntmY7RDbKSnrzaEdKWkN3VBrFjHO/4m458uJ0xd+7VD5t59jpGW5xZoo17yIRLti1DZCcSLqEfs056JOcm7YrDTpK2bgyXdmZ9yKXjSzllXyLgNbPENZ8lCKxsQvJN2X6/Urop3lKRLuweX3CRELGk3ztqLh/G5VelBkTomaZ2h7ffLCo+UEiT6Z/165b/+FNEluw9Io7t9qyT+E7Q7Vy/RIpQp4+NL26segyicu1+2pAWFgVJFv6df+1W4ZS4ohJFgHaQMx8/2KR8mXVHKpRhNhYmRW6HF/ZKt6MsSi3TkdeeuZpvuuN1/jI889wNsAoyiChsPa7ES2FAc2OaVFGXzbNj4Gos+gWXyQ5xwjtmRlznaNnRrpNqkF+bmZmYQY6T+Ie/UQbUXhWhiFQ08YttNTUs1WQFvfBaun7uTpdeYwiqAXKubVrnErlqadGPlEPfGx6iy/VW1QKXmfISFNJxLNNxLq2qfMR37Wjj3Wt6IowZcfM0/1Nt0ZXZbBEWDYo9FrNCiznqSyuiUY+ibsvfbp7BGup6t2s1aLsHpXxnP81i9o33yFkqyU/1LKIz6XnjXSOJsnTlEVflOXjjSdbeXRrQN+83QfcVguswtzfsrU1mYCJe0zc9qiG7SIvUpYaP2LntiiTHs4V0SXjU1M4em1K//SVhMyFJok4Z2Hiu2sVp9qFq9BqxR3KOHLvzhnf9vILfM/rr/L83VNUGqoDu2HPUDSPzByifMEDzpaxrHUUTvbcJK16/N4sjhZgQWoBqRGBhMpaBGu2KM+Y40yey/BgKAejH3Td16l/XldWUdmbEYDWspnQSqy6RyYsHkpOVTDdsfPG5JFA/uHxIXcOl/zy8YK/f6m0eY/NBZZuYdemf3nIQqL6Zo36S6+7Ko8I3eJGLNt3s1HX1+n2FWzPOO4oQROZicXcaRoo7wT51v1YfJf4/JW6Xa74jvvZfv/mQdbXrjzcmYboxBb8YBwEFdsgOrv/w6s8WNGAiC4bWGFp19atTvfhuuyE0QuP0yT943ws1ikVEtpRBYlwejwfXBqoUDb+cNxLkrMZapN+M7K+RnofUEh+xendyUScQUr0Hq0z3ipF4fz0hNde+AD/yIde48PPP8udk4IUoww7duPIToYIu2qUopcyRGUvLSIolpu4pHVrEdpeFKzokpchEu6NlwHNcJ9aw+uMlmHZYKoFzdC0eJg0kegmtuQVOEgZcsNm8ZWCoBQZEIRWZ9xaKqCe3RhaVHozVuJsFHelOJyq4yYMPnNH7/M0hb/+hSNvXznHg+Ftt1hRyEiXB3oIpGGodHxXYaPguqF5tLbUN25ycxiCso0CtbxnUQl30Lsb5yt/kn1xO3D2R5BId2eNKFXo1byeitacIIq9kUeQddxBR3WyyGnyIg7RArLRahwn6ioUAzVjn8YuY5ThUqFRN/SY43eF8uhH9239xfUIBs3SbVsmddHKvUUc4RMq3Rok8rjm+fXV7p+b1tb7SfNd26+opb+nb55FHB8lz/Lzet3GWJRxKLR2zA0VRwje2o98+MUP8APf9nt4494dTkdFR9iVPeMwUrJFny5wu6T7JCsETvdFtCtJWxUsoQi64HsPEQ8JoRF0iBR8N6NPyRJhKoo1W9wi1VAAkWOxHi3RXUIn8kVEIwFMxyE6owehsszPGjYFNnNYiiJ5sshYhFvS+M67xok25jcf8PmHMOyfBRPEMy6j1+Jc8d+N6/guArbhKwh5SMS7qpdQuj2KwuIGsNaObFyZ5cNkc50F6a33I/2v7kttTD9nRj1P8euh40UBPfoFuqLK/KClnwnY4BSDwQgF1fNzZYuk32VOvs7xRCuP7lNezy/gmgJZXZCV/V6HZyn7so7L88u1ddtPoodz18/SLG9eXKfEo12QPK2bWXQ17wc9LYk/i9JzSoFRotFOwSlhezBv3D454aNvvMoPfPhDvPj0nczZiPL0UaOnpy6oRZKXWK2oimI2UyR6jahf36B4Hk0pAhaZioJCP2IgXolK3JVkCXBP7S9FglyOhAUgDkoqiQpFJLgkyjV3rZQSVlwHzBtliMhO7+nR739ZGY/svDJEwpoVqDWsMXNBd85H7jTO3zjlqTLx175wQbM9g0QkTr9q0tPWp+kCxteA7StP0Nd+e+WOXsGTJC8pov27s/ou1hUiqyxuLrQcDIZGycG16M367+5V9zXt+SAL32MeTZEy2hI8SCok73zP6qJ/Izke8IQrD2DlJeibeUB0xHUXWXP0k1e6ZegwrrsRkUdBf3/8kbVQwkATNrMWpyFg0iF68hfEe3pJeGst/Fk3fDaaRc3CbFmdS7w3+oVWRnFU47xcZeJ0dMYdnNw650OvvcIPfdu38vz5CUXICEpBs+haSx6EtCiPHvf35RQ9KNnEJkOE6YO7s1TptmZ0PlSlZ6xKhGZTHxUZwYxap3AlrCGcQIk+H4HMjXEYsXpFsxouTxKilptKrAWK8biXQQdEordo76vpHvNvZozjiNewtqVEhMNFKJRo0NOi/4qo8tIt50deP6HIxF/54sCXppniE6NURm2BV1Sydr33g+/KIytzk3cKZNZzPnpXBAWG7ASQ3dopmaia5FWJa3f12zd0HPS1chZCEJldUmNkZzIVBrK9Q6KN5hbV3q7gGt3KWADRKt8Q3f/dop+IWfaSiZaag0VekbkyIyiZoZ2y3Lmrxx1PvPJYfLzOeyTakMWFWSLf1+BFLGK7ZtWkpG+pLO5Hf590aKlRfi4lLHTSSqs7pCHwvZgJYTlLxSyOdai+no8iZBWsB/dgNkObMGngA+d3z/nWl1/mez70Bs+dnqEem2gsY35XGHZDWOKl9b/kub3hblidMLdkWGRVMKKpADe9TdyjYtUzra2nNmsgF5EQdM8KTMdDYZchqpJV8Tx0WjG0jJmumgio6LKJfO65I5ofkUp54VIibV3wbKEnyBip7UEgptLv6LDossFHhWfOGv/c6yPn5cjP/+rnuDheMR0rO29YcQ41UWdHr+8CSrrFpiRy3bgjnj01jCDbjVUZZ9P6qJy2nsvTP8AQr2AlSuet559E1/NrHc5TsUPvxL7Kbzy6S+LXNntHPf15UvnE0Z/RXEiyqZBtiNkAiCHHQag/yvh8/eMJVx6y+HMCS1+CrVcLq3B0bdrHsqAJDSMPNFBHP+2+9Oa7Gi33vNY4+9aIJrjGqrTyk3uCkPV5XxoAWTxqzSMAsgFQJgupG2c75exkzzgUbt+6xYdfeI7vfO0V7p3tEWaGsmM/7BiGcFnKoAz7VWEuYeQ829Vrj+4UaHVJE380a9JsTaizBrobYx6yx2dtLRBIKYHUsj9oNKWJrusikuHY3qhGo7tSIgtPZd0FVbNSFnoritgcWsqanJEIROkn0xHcDb4cZtRqDf7DosZdFagzDbh96vyB14wTP+fP/d2vcLy6wppTrWat0SoHwvUU9f7xHS1I1sJuyfPMw6V5nKnSUrH2sGhwFLq0CgzuKdAaFucLO06zSms1Wwaueix6j/YKt34N35In9JDqNqq4vHbDy3SE0vuKZEllF5nYS8kVDsNAyd4tjzuecOXRR5/MjFl3sjLNwAK90q+LdnK2USYRJouGKuG7hzULyysFZAj+W/LU83BlYn9gnv68hlV0TRclKmWtQa0WR1nOjbnVyIS09SxZt5mxNM7Hwl6dYRx48Zm7fOcHX+XZ0324Abs9+92ecTeiWgJdFEmxiM2YaH61JNoPrQIk8kCstuhzUQQtA9ZaFPulj4yEkKsr1qbIfhx2eS4v0UfCDBYiNQ4pWsLToUIjZWbcYbUr4nRLFqvY6ADPNVLUEZBB0SH6dbgqMoTioc7BxzRPwjYRy5Buo9fY4FrikOkaLR/PEX7/B8+BF/m5v/0mv/6lI4Mqe8nNFQ1BqHjymJJ9P+LIhmbdTVh5Hsn3Lj07LJoPx3fX9Iais7nV7BvrhqZ7FUl30TDQPJRH9RmzI9YmsJrcrEAq+yhKXLkNh3SLI3q0RRsh7hGJihMM437M4tiJZk5p/bWKMwAlIiwpV5EF/fi78rGVh4i8CvwZ4AP5PX/G3X9aRO4Bfw54HfgN4A+6+1sS0v7TwD8LXAI/5u6/8HV8Uv43Ix3IcvxA2qewLktPjXjXosF9a3kIK5fIQ0pWrua/IaCe6po+HL0vZBG4fnBUrZGgBL3hbqafV4uu4j4jVhFmbo3O03dOKaUxlogcfMsLr/JtH3yJZ8/PGIsz7vac7k/Z7XaLixGRlHBdSo+ybIySpLsxLGXzLV2aqDrVoeBTRYchq4MbvaViRKhaoqqeQUlCY8WWmp2cK6uZ8g/ULAMQxwciQuOem6WnQjp4L+t3dBwikcwMPT/FiRCiD1HYJc2z+c2AjEGWeq0wTyzp70VRL7TakFIYII6etIFyMvGPvX6b3fBB/uzf+jRvfvmKowiDwFSV4xznmvRGjkV0KQtwQjl4kprmsWGDxBRocQKfRKIGeLSYpKeC99emL+NmWKvUarEGDtY68pgwm7FUHqIlmmlvUPI2jJzSnAh8izrS1dmQpZ4JdrW2qAIe1kgPyQ9uD4svZU13f5zxjSCPCvwRd/8FEbkN/C0R+T+AHwP+srv/lIj8JPCTwB8FfgT4SD5+CPjT+fNrjh5d6cSbeZzbOWnCWtewoGbUOtOWpJlNxiEsm3EJ8Q6KDCUUyLWeFb7wBSLROlCJz4hmKyyRhDmimdRmgTzmGl2tk7CEyq09vHbvFjsmvnI1Q4PXP/Ay3/vGa9w720VB227H6ckJpyenQCiKqJoMhNKVyRJVaW0hTHWIozKbGQMDzbIuRTIZTYfIm0jeJVohBjQ3ASEgczseUn9E8lkfPexqJchYqy24Cw/lHd6LLK6hb/3rgSBclUAxmf6u4w4ddtAqDBkt84Y8vIy8miG744+GqcB0DG57r1SZog2Cd3fDGBWaK+MefviVe9Rm/Nwv/gM+/bZxMozM1bmahHKAq9qYPAlUleUaritvsQ17uyit19CYx2FXAtUjilI9oxstjs6IAr2ayiQ6s8X5nxWxint/tFDMG5cl2dWYOzq67ArjEYjga15J5z3MBGsdeeviUnWXs7vm6z74HVIe7v4Z4DP5+wMR+RjwMvCjwD+eL/vvgP+TUB4/CvwZD5X5f4vIUyLyYl7na3zOiiDCwldqU6QMkbRDEJXBNOfJYZ2MkK7FM98jSaJwW+KgIxnyRPbMHVYP2In0LLyydM3uJ5YF275STbU6x1rxGptrIIqY9qPyzN09D4/3maYrSjnh2195kR/48O/h7tlAKcJ+f8LJ/oTT05PIGBWJqEqmjnc3ofvm4VolPyPBswz5fQxlKGOEOL0hJULY4TbVsPa6buKAxRll0pjNmLeuAKILOS2UEOkCmAiiJbmBCE2HghsjWlNKHF5VIk+mv0a0UMYdaCbPlRE5OYU2Bzl6L9oZWq2UVvFMdx/GAZ8nfG55dm0cGDUmkvHSGNIuF4Uf/OA5x/oy/+vHPsnn3mrUwRkGZyjKcJi5ONbgEYDul0SPFcOSq+oIwtMlbCZrjw7isCYnjuuo1jdyr+6VTgUlGgG84m3G2hzKwwx0WOa7y+fy76X3TDzMr3MlzrbKvD8pK5krZEZ1WYxjVxwlz++JRLHHH98UzkNEXge+D/gbwAc2CuGzhFsDoVg+sXnbJ/O5a8pDRH4c+HGA/W5cfM/WIr05oJ+iVhIaS3YhD/ehpg+bVAcAPaAGEZ4M3kMCfRRBx0AieQfhupgEysjFCwTUy5gckZKw1TKjr4ZVMpAhiMjTQTjfFx7Mzq2zcz7y4it8/4de597pDtQ43Z9zdnrO6elJ+vW+hqZFGMcRs3atpFsTkfQWgOIdKYXgWdasqGiHG9HMuBplvw+o3LmHXl6MxqHXtXW/JTibnLNpnhEa4zAmbdLDshakqJBkavQP7zLfmjEImeoOw0n2gDUDZqQM8R3Oz4MfmS2y6Nxpl/fRccBtj02X6FDQsQVaOBwRa2gRigomBVdlL0KrjbunO37/a0+hQ+Ev//3P8ptvHVE32lCz6bJk6oUvRyyEos7ixSQ5pHkiBBaX2Vso8NoSlbTkRhcF0mhV4tCpGq2h3Bvejovy6KkDIW0rf7V0c3cy0hV0bdcPkRO0ieokSrLe1jArqF3yNbkuQp4lsyiROKd5kOhg/7jjG1YeInIL+J+AP+zu97dxY3d3eY+titz9Z4CfAbh9furJKoVb0hq1NobRGHISzaKy1ZovPR36mR39g1Wi1ydqUDzUbdm4LUUCYidDfU151CCyyhAZFxIdhzeRgVQgbgiVcZgY/Mi+zBQqD+8fKAVefe5Zvu+NV3n+/BQVGE9OOT055/TkNPIbJNyAHtUhGfZSImkrrEaU8/ds2tZa5kNk4VedqXNsyn5shGinNwWRobu/y/z0hKbggzYnjnV04IRydYm+q0URBqQkN5BRq3ApQ3mYRQvB1uIsEi1Cs4rUOErTWxKfRaPp8TzB6RicDMlSlx1tPmSOSSBBz3CtZEtFbVEHJG1O42AMBcSVp+4Ufnh8mn0R/vePfYY3vxS5H4epRy1Y3QU28D/lh0QiLutB356Kpafmm62u0/peMKv0bE/rCsUqtU3xvtbwdFecjqwzZLwsxmbbvMNj6S553wPJdyzn1Vzbn2GMWCOSizIp0fHuccc3pDxEZCQUx3/v7n8+n/5cd0dE5EXg8/n8p4BXN29/JZ/7mqOfZdEyBDrPmjkPM/18C82N1BZSquXi2jrRQTpHZKUERNQi6FjC6pdAGSoS1qiCZAMdrUTy1bKIa7qRZ2OYgvDsnR13dw27usDsQBmUcRj4yEsv830feoPnbu8RiajK2ckJ+/2O0nMXcEr6+j1S1N0EkKhTKCUiFqyQtW8EM4eyY9Qx0QNkcQmmA1rGRcAln/eMFi0VnpDJZJKu3JjCbhiNkpGbgINhFWtr0QtVVgsaDXwjvyOSsYQi0RgoXKfINqWMUAZA0GODsWBjgfEU9qeU+QQ/XgR6mo+ZgxM8jxBu5ahCm53KHKSnSvRQNeHeifB7X36a2+PIX/qVz/F3PvUlDvOOY208PGYNULq2aaOWOcJaRkEipTtIzUzF9835MAvRHGfxxDT24xl6yvjadKgTnZ1fWhRHv07+xx/RHUs5xKP7o3M/G9J0lfnrBrVaTaMYpyXach7N441vJNoiwH8NfMzd//PNn/4X4F8Hfip//oXN8z8hIj9LEKVf+a34DghhnqtxnObsARFseWu+8d9igVqrWG3M08Q0z9Q6R8ZiiwpGF8U0ogtlgGGAYRC0kHUaRN5D8CfnzgAAIABJREFUHq4cqem+JDf1FOzOyZpkUdXQon5gus/F4W0KB4oIu7LntRc+wPd/+Ft46anblOIUHdjv9gzjGJme/WzaLPFvLdwFUVsqWAeN09trP34gJUt1SHJU+pqg2jmezklENaX5HHkHTbLhTERxIncifXwt6BDRHpRIU89ksDxqKbJMXQKlCIjN4Yl4DZfKFNWcII/iryB/ldpg3EVvU/UBLXtcBtiNsXl2J1AE2Z3AUGjTaSShyYCbIEzI2Sl+eYnXGSkZhdITQKg1wuPqFpzMYJztC9/xgTNOx5dB4Jc+9YDzcebzV5WLy664ey/PzEY1p5hj0vBMx+2HMLmumZm9oYMLgY4s0u7JiE4oo4iARTSnrFyGFKAgvh5qTpZYeF6z246MCse/+75Ig7g9kdClI6AV0fSs08kqahU3RVoJkr+sGdmPM74R5PH7gD8E/JKI/O187o8TSuPnROTfAt4E/mD+7eeJMO3HiVDtv/FbfoI781SZhiPd8YtTwo1xniLvQQuDsmhYN2OaZ66OE4dpZqqVmuxVyQiLDgUdAnlIARkl0EdnpF2h1ljfxJHiEme62PWWcJEG7pg/ZLr6MmWsDKMyDCMvPHOP7//Ih3jp6buc/P/kvcuvbVuS3vWL8ZhzrbX3OfeZWZVZVaZsqmwBPWjSsUB0wDIdJFsgRAPJHTeQEAK5RwMatAAJCWTJDaBTEnTgD6CFRAcLRIeGbWHq4cRZ9+Y9j733mnO8gkbEmGudm5nOzJsydSuZqZP3nL3Xe40RI+KL7/siR4hm3GM+IBPHsFNLJLoJj7NH5TagubUCMZHiahtzFsESYDJRcQjIPUJudboFAXPgMoQ/hnSUXa13RDtR1EyHQ0TjdLFyvT9upKvqpYVNg1Nz86CrAaqtVRfJ2X1S9Hq9DyQl0rqg4qMWBLQ0OK0WlJYIjxdkWUCD2bAuJwv22kz1UZ321Q236a35PBclegbTav0AbE5JeCTwT3628Jf/me8RgvB3fvjeeDB1sFe9CQ1lMOef4F+96XAGot02/NSp6Z3n7AHMO/vYyW2H1V+/ZRTBDy8Z82eeFVsSdOBbM/H8sbxA+SCbMB6JC+jusuxZ0tyyD2vj9jAY0bP5zi3Qf4Prl+m2/M/8WDV2XP/iT7i9An/9F3wOSi3EckOd61BKbaR8azlFN3QF0N4pxYLHdS9sdWevlaRqHZoULYDkCMnA0pgDKdtH0bUTkpUsJP9CxfuezreIGpjYt/TBaDtreOF8giUl1hj4/OPP+Gd/93f4M59/QkpCzImA6VPAlb3zxPGVMpl/QUxQ1no3DCMoKSbDLFAPArZhJWT3NwruiTqFWuFYOIISamW7PpHXM7VsB2gGcrRaURO7zcAS8Fp/TPm4+k7BSXKdHJNraBp9+IhKB3U1mfGMBEXSYpnf6KZV0WYEqNoIaaG7CQ/bM1xeW+bQdibjUyVCXi14LAPplcDO2OuxM0MI5LzY2IjeaVqN5yFCjMJvfbLwL/35z8kBgryw18qPnhqZSZjy79R3sogQnRkrZr5inidqo0lv0vhZfnCA3Yefiz3QjYfjAWcu2Lti5WuL/wZ/THr6ccsjgHQOyrs2/wrvwFJmSWtK2xaVGNR4IF0Y8ac89895fasZpgN42XcrVYah9qk5SLjfSFQ5hMOIZYxOrYVt27huO1uptOZaDBFiEuJiXYsQoweJW89KUiA2ISXMQQwhdjEgLipB8aHXzorsT2j7ksDOkuG8LlxOD/yF3/5NfvvXPmOdwjgVlnU5oq1lLzecAM84JobRO7QuxOVMCgnUkH4ChJiMyGWURKIktNtEsRATdXQzPmYYycrT7mW5MBRSWnzB2e0FCwbzFLXFHWjDixXBsrHRPcwprXcDP0OgjWYWhf6ehro2SJK/1uEwieEGhEAdynJebWiVCBIy7A2Cos9vEYVWXgjeNiUOaF5aLSekdVMOM5DSrfJqNuluqJkr5WDdneFGTJIjf/Y7F4p+hxG+YMmVv/MPd56fp6nPzVPVJvhxm5MiU5vTGEyg+L77dl86GlYWSUZGCwMhEUI/WMrWO/Gui96sqe1AmWK+4faD01vGOSgySxJ10NbKLpWBBaiGcGc7od2GaQ+IXYmpUzrkEUj6J1O2/GO/xhhctx1U6G2w5ERK7eA4SAg+mjAcFndjdErZ2fed67ax74XWGjFnO5EnNTeFOW/QFvpseA845JZRDCTDWZ4pGL23z9kdimohamVJthGbwnc+/Zjf/Y1f55ytRMoxHaUFzDo9HIAnzJT1XpUqxLwQk3VOxrgNYAoh3qjewVvV9IOiHNS9THQcnr86Sxwg58W0FqMZPXxqZpy1OzDBoYG5bqCj3oodRucPMfrGtLvOtrZRu6erOtBtKGfIxgExUVZivSRqLaSYGfsTgTNoQ0OCpnRthJSR04q2Ai8d0R2pxTgfopAjIZ0BRavnb+MGMCpKzhkA1Q0R4XUK/FOfB8poKM90Dfz+DxvPG0aqkgPd8eTAMgcOUBjvgItnJrN0cY3U8ScSQyaG4O1zLHgE94+9W+cTtpylyCy/YXZy5pyf2764B0Xnz9DbIHHB5v1McyR1DlTvSu2D3oXW1PRb3/D6dgcPVZ5edlpTSm6saz5O55kihmDT0HK2mneMRm2Vsu9s+0YpxVSgORlQmIIxiQJIstKEpMhsUij2s6Y27Cla61AihGHy6REC9E7bn9H6jkQlpYykxHc+eW1Ct4eVJQWSBw6wL3gSwVRvStcQbmUTWFAMKdpzR8u6rKY30G2oQEyEYG3B2jfrBoVs7NYQCMMo/MMfT8PsUDiuoYOQFpQp7hoHTf0opMbUkRo4LNG4B92VvyYfx0BAvWEswQcSBW8JSsyAu3CJibemKFFrI5wmFwIrJ2sljg7Liki27+nkjNberEPz9MaV1pmRs2E5WWjbboO/gtPP1YJ1zpnaChIjpxP8uU8f+OHbwVZgCYM/+vLK+2d7bbdyxD6IEIK1+u+zC//vLFOEiIhlECFE+yPZSl4nZAXxrGCWLD+hK9L7Dc+YPjEMtaA9I/VPuC/g2Y6whMSQyBLT4QMz72Nzg6IZcXdxicU3u77VwUOH8nLdqbWzp8paki9wQPXYeCFCzhnz+TURUi2VUgq9dY6ZXHeZhgZP84KaCC46EUxBM4xmQJdY1kdMiYQQJZFaQMuVfX9Da2/IAvn8ER9dLvz29z7jNz/9iDUmcoqmXgzx+IJvxsniUvVwAHzTVCel2e3AShVVRgyEmEh5YTTnCgzTsMypd6ZiFQdUO9NYWJwYZJ+Nb0I3+xGJnkXNLoGpXnU6SHTHfNykR2K0bGK490UM5lrVlJwiMZmlYW/GGk05kHxTqdpoCXsqV9wOpT3vxFUJOaPVSiBSgFoxWfuwLpdTwoNENEVGq0hpSIgg3Tgga2Zs1YKkeMdEBylFU5gOWAh8kiN//tfOfFF2TkuAsPIHrXNt5l02Hdju26MzYIj//bCi9B+YEDkSgpdrrp2iCyEqITUXD3bHNMyCcLg2ygJHPwKGfV7daAgHxnHX9p3BRCfZbZZRw9ape8CkkJjzjQ5sRu1w0ParGjxU2fdCrY0aA2UPR/CYUTeEQEzCuiTS1CqoWtu2W5tWkrNRg6f5QawlGMVUs/PfYv/ViBGYIma0EyKhB6T74tFO297Ryzt665xOF5YQ+a3v/hq/+xvf4/XDA6ecyMkyCnFOc0rpSKMBy5ymo3hXV/RaeTN6N4A2r0Sfv6K900dhjhKcwWIcnia3LoPi1ox3BCTxvH70yREJpHTnUdEHMSfvGtwZ5EaT/iuDGAJRI6158NKEDu70N07AEg9AYgpky0Kgd/MM6a1ZW9k3hJVhG2Fd/ISPSFMrmxKMshN6h7oZBiIg6wPj+sckQKOgKRDDQutKv+7ejvY6RqesHXIWchO+/5j5p3/9kb//o413287DWSgvmAfKIQy8LzGMpAdO/3eLwHv5gzFuI4R0c7kLyRhtIuBMVetv2zyYIdYJmSAo6FF2To7TlF30GUCcUKYzM7FVxHQ3Mp6OmWsnt7C0MSM+N8bD4m1m8i9+fauDB3gm4Rxg7YEQ+gepGlhWMFoneQAY/uFbnWjMu9t1R/eVqQHQm6DLLQmtKrox8ixFtkn11+2J55cv0bqRw8Kryyu+/93v8tnrC6+WhRQTOWVStDKBWUp8DeeY72+2Z+/TVw0GbBqOwPF+JpI+ffxVbbFaZXSrf4NgATEkz25MBzKfx9ip6YPXcIxGVMcvhp+9wYh09OIaGautG9BaO8RVcwPhBDwJZls4MQgcg+jDMomQordAFY2B9rKhT88GMSwZLZs1uYISRkOWhdEb9B0hQna/VQUNgZAXU/yu2To3rUM1ZesYYs5m2GjGHAOvs/I7H5/JayalhTfv3/JuE5rctET3l9x9VvffHwfvZnZaJt4Rj7EXwZ3hZiZzsKNFbt+5+rN8Dc+Y39fshE2vmJml3O5/u4/hMZb52p8MKSMhknMkZSGE7h23b3b9KQgew7+suVngFgC8rXYw+WCqWKzd6GzB7qpHxwFab7QeaS1Se2RvHYkFEaHUSqmN2ga9B4ZE5nxZk9x3tus79u2J2AaPrx/4/vd+jY8/fs1pjZxPi2UbwUlFzoJNOR+6ghSTdST8FADMjUydrZoiMZtmZIyOjG7lRUiWEc0277il1yEYgBmD2GONzhDzQbWh04J4Cg9mmiwix6KbNZseaL8gmHhwYEJE3J8ihGiApgfcKOKZk7XBe6/W/ZpAbB9uVehdAVW0wehm/ByylWTLshi1XYSGonthtEZCkbahS7LSdOwQT8j2TEzZWvBlN3lrTj7sHIYUINH9pA7B1KYdb0fHwOMCnzZ4frXw3U/P/OCrnf3gZUy2qStm/bPzXx0eG3qsVWYEZfZuIHjGN392u7Fi3ZIR5gzjcZQwIxg358ZfstfSW79lKf1GT5/iUD0CWTiA+bnukElt8N8JVu59w+tbHzwmTmUpZDgitxypaDi+ZGMG36L1PaXYHL4GpXa21Fj3wO5T6FWUppZOl9J53itbGdQWaCrU1ql7oO6DulX69QltG5Iirx4fOJ9OlLLz8fkjLqu5hBlJKPoqi9Zt8BJp+CKe6at2a5vGFAkpER08HZP96bV0TCazPqyhgtfUwwRV4m3SgCIxE/PqKLDY59NMCmypqg17wmd5gG0mMH0PivubYgY3AVSSpdg63B/J6fwxGj06WFYTRAzcw3UkjpWEELEYZwzXMdvDvaF7ZU5ma06Bz6dHyMLYnuGlIc02lYZEkmRYSFfGvkPfCWFBNNL7cL2LGUxbTeZdoABpgaodhpBD4BKENQ7+wp954I+fGn/vB43WFdPpCNLF2JspEYOAzol+fvq3bj4uVampU2pjyYnSvATpWOldO7Wa38Zo7ciIe080hFYqZSvsIUCvAJS9UvZKqw2tA+3THb3TarNW7dS23AWPKCBDnLTXqD0ShttWBiOIGa61f+O9+a0OHpZ5W+SO0/r+CB6GY5jgx249HbfukWjVgQxTW5bSKKWTY2MPVhNa4OhkZxqWOtj2wrZDqdAZ7DXwsgtbGezPz7T9PSLK4+OZ82VFtfKwrGYvuOSDFn6UAyk4wUi4H9Kj3NiAIZq7lqRI7Y2gHD6tBKfWqyApHlhPCMFOIjUhmqTsgaH74efkIgfVrE0aj7RYxHxArI14e1zxYDM9rez/7XmsK2JyeRhosNc1yXcxiJfdHoxmUoNPw1MlJjkwGwP/jFE7ekXyYkS6VoBGICHnM+OUoezo9Qp1Z7R3Rl1PiwVRZ3WCO7Z7d2nUdmSi8/0BpJhoDKIID2vm46ZU4M9978KX71/44qkal0U6dGPmotbFsM91QOi0NBhN2HdYgrKHZrQhsdv3FKDDvle2rbKXQimFWit1dGv5xoEkZRMhBZMD9GblxLZtbJt1DUsp1FbtvrVaEDoEoZ3W62GB2bvxnWqtBtwq7jkbqJKJQQl0xijfeH9+y4OHkLwDEee0q7s213H9VGmg3XaoserKXtlSIYo5TFngGNTWyS4RqXWwlZ29CnuFro3SI1sJ7HunlxeidNLJRG3DCVKff/zIq8cL1i4274joLENCoOsgEj94/dHLjxgt45j4S3DjnTmAW5J7YEi883zgkGff8BQcoAvW0vRrnvD2idpuHsMo3QcoeNTgTvRygFUdodfemOSlmMQCnQ7aUNfpBIdiLDNqtTogZ2SnQCDGTO+V3gY2fjJaVyIkRAtooW8vjrGY3mW0ytHlCQk5nZElQ93orTCuO6rmzqYOzM65uxYkfXJeNPr/ETxSMvAWYUnCd84ZjYnPLo1f/yhw3Tvv64a2jIQFIZg26DDdHoygtL1TkmVyNhwqWeBXRXuiRpM27Hth23b2bfMAUi3zG8pICU0GbkcURqOttjVLKUfwqLVSWj3+3pvhN8MZtUObHyaD2hq1VvZ9tzXVuvNMBKUjJGR00vgVzTwQE4XZXy2NvGUeDu6B1W2+p45O1AwurnptTSmlscfdvSLdH6Rmaiq26MW0HqV29qrsVWkaqD1SamTbC/u+oUDGpp6nEPj48RWfvP6IdTnTGGQ/nUy9CxIMDIsSj5Mrxkj2QBBE6IJlJwTLqqJlKhKidRImQ0mi6UscUZeoaDWdh/adlBdLVXtFsU0eouM2Ym7lOkwOP3BOxphSujsE3+XoM3sRQ22PNp+lF2aN2LpNVIsiPvJwKmibu6qJ2wA4l0RtBEAAtO72IUUhnB+RUs11CzV9keCk1ERXH0pVFNYT4dVrQtlQ91Kp5R0L5vZGcvs0WyxHRnUD2r2oUcghcI6dVnbOi/LrHwf+wZuN963bW27Yi5idMe/ahG65bg2dpJVKZZPFMKpRoSeqZ1+lWvC4ejDY951ajVrfU4dlEOns1lBmNFsnFgAKpe7UWmi10vZCL8UyDyeS9dYZQ/2/g0plD5t999qJuROk2veiDRkJeiXeHTK/6PXtDh4wGwg2DkGUoymlN++JKQqaJB64IeMTCe+tc92tjux90Hqm1M41F++KeGk8zOilVChNaV2oXega2WujtWrej2JWgZfzhc8//5zT6Tyfipgz5rjl2YX4QKAQiDExMffgX/x0dtcRCMtqp67PPBmqtjlCtAzLRX5DzXhXRyc5o3OI+JwSawkquJ7EWopTcGUJii1qS34maGrtWAseN9vG0TsSss0I6c0wiiPrScZSdTvDgQWS2W6cRkDi1HX/Zqw1q1bKGBfCPVNytnElWhnabXOvF7t93RjDHcaWiLw0Zxrboy6nR7cJtE0kXiJOMtdNtext1TCDnc2+eciwSuP7n2T+4dvGm+dKGd3eMyaKxFvpM4aOAY1K1UwYFRkFbQvaVtoeSE6sa61TSvkgeJRiJUNKiVEz2szTZPTOstjWnCVKKTulbpRJXajVSHp33ZbWxtGJMXjLXmnrjdgqMWZiSLQRKbuirRB/VenpzJRZFZHOOFyPrIXovJgbgDhbbB88gINSqmx+qvbeuZbCkhNLmm1OOeDy3k04VBuWFk7kPCZixEhcoizLwvly5nw6HSzXdTXxXQie3SAkl7kH37zBQdKudxhNSpAycTEB2XQMUx1o25nYwxzybUQrA10nY3Uk9ffh5OQQbNPTDrXrLENmeeItKg6DHH89fXSjoINFGO++mFX/oLcJWnu3a742Ge4ZYt0NHNDd9s1LG2OWjt7JOZCWbJ6lXR14LJYF5UQ4nSyA7ldGd0sGxGwB4gmRhqU0A6IFONpuLM6qhneom0XpjVQIuBWBLxF79bxe4LIE3l53Pnk1+ORR+eGbnd70wFSiczcUAypbU+gBbQutJlrN1LJQ88Li5trqvrvmR2PSCeMvVceAIi1nH+DdaLWY8bWI36dSa6HUjVoM6+jdpQR37f0xODAPWqOr3W5dCzGtpLQQY0Z2t1mohfQnJMn//+DSA9BRzBbudnmYEDFPBKxJO3041bsPh8rQg0ZvgVINYIzebZk6jJnXzISlK/RmBVNMidPFCWPA5XTm9eMrPro8cjmd/LU6At/V/UQXW5jBbP4UJbkYygheyUVWBnZqcDG9DlR87MJQ1AdFc1NdoL5hJ2+DO6tCHXrTmrRq5YFrV1xL516aeuBIM/MwerVT/fvwAG6kqe5nGd5hMWqJuusYPg3e7je0QYAULaDkfPJyBdDhloamtYh0WjOPV+KCiJPAcE+R5UTIr9C2M1qDdkWaA4HrmfH8hiRqHaxun2dcVoK351uxU3oyLGcQiOJtWw/Al5R4XIQyKjF2Pn5ovHkuPG0dHRY4x4FZ+QpVpcdArVdySbSS2K+ZLWd/77ihVXdZfDH2c7UOCmpZUEuZXipl28lLtgMKHNdolFrNv7fWg8Ku3ED3aUU4+m3gWHdVdquVGCvR2c7TCa3VSgy/oq1a+wDakVHci4OQW8fg1nvXIzWeBr5659E4eRPVZ5DYz8Szk/lYctTK1u41UHFxIVTOicfzhYeHR3Je+OTjTxCBfdvhdDpk7tGnsqUcTTg2NTkeACVG1L1B1GfJBLe8UwdRkeEUdgtOB0YsgRwX2xCjEXSawcgtIARLx01W79jQ5DvMuZJyszI0W8PmgKwFyVsVaEzPaX8YdDqYDYYWe7wx6K3Y6w0BiSuoSca9n2SnqZ/CiLm0H+Q3L7Xw9yFOJhNJyBLR/RlZz8j5jIRXsF0Zz+8IL++QVunaIFwt8EkyurgH1HG8fy9hD0+SQAi3FmdAeVwTpxhM7BgGpyy8e65uunMrjY8B1FiGGirUEinbpOi7x8rR2tUDeD4win7L+lqs1FIco7JApdyyCvPwdYapZ02HaRAeoPTOEtGbBLE2SmmEsH0gyJyP+SvL81C17gfc+B5wFz+OWxroc+sc4KfwJPBMzsFP6srYST81Ci55Op5fGYfPxrIsnM5nLpeHI/3N2ZibtdYPMBcdNuV9ulZzAJ4JFSdeBUGjubkjwYOMUaBj8PrcY1kI8Vg0Q9XOy2hWckPNcuDwlhhGI1fXvxhI2Q8iUneF7oeftXVtuhso34yKnEtzQ5islOiKjOGjDB3TCILNjTLejQybXI929zTt9j260nRuYkTI64NzP9QV0oGwLNAKOqq5jC2rZRt0WDIxfoSWK9ChmGS/j4b2QmiN3uthdDzf4/xv73cjHzEjIILy0Xrik3Phi3eV5IOmtO9G6T/W3t1n4VcHqnAYAM0Sy0oLP6wsuTs29yxF59q9MZzDoUuar3dmGrf3YoFp3O0GnYC2cDx+7wp1IFSOAeR3QWb8ygrjgDp8YXNouQDfhx9AV7fadeICRw0CDgbqwQm54/ode37yBNS/OMMYzOeTYIOaL+cLp9MJ1cHpfLJN0SqPp5UQArUN0pqdYWpJTcrp9mxzdKW3VC3lnL6cYupcNfalOBNVBUaMmIvYcPwl29S1lG/s1F7viEeKtSmSj17Eswl3fZ+ch+gSf88qothzI+ZjMeeQiLNPQzAjaKKpfs0r2PgnOSdEO9oLSW2amsyOkWsxgruLBedhSPAJ7sMecrJnRRV6ZSzGGB29IPsVOb+GmJBxNY0PgsSF8HCBEBltp7/7iuag7hge2Py5e++3Q8a/knHUICCtEnrjlBPnJSFqIHnrX9tkeltFc9XMNStfC7Tzd95L45ZA6/15c6xFh6tvweN4jvsD85ZpMpf5ETRut59zaacpnLveHG3+wdfe1y9wfauDxwCuDobOWn1eMjGK+4CCfTjiqdicgH67E56tTxWifPDl+eFg+MpRKllXoA3ztTgtJ5Y1I0BKkdIqowuX0yvUNz8hHSSlEJIN9vFFE12iP3TYJnBAlTAVsNFms+bFSxlsdGBMSC/2ngT2l2fariDRJO8hQIoEPEOZm2SANPfimDNsIy7TtjffdLJL/d234RwMP0WH2xKGji28adBswr4xGlo7miK1F7RV0w2VTqP552kYyRAb5ynBgWf/Dqc2R53OPbo/ZgHJmdBBs8J+RVKidwuIxAVN3TZS2RFtpqtZM6M0WmvGWVHhfuQB891O4NmOdVIenE6J+FR5fTnx6nIGnuhNP9i86utvYjMf7kE91tN9qT2f78iO79Yd87Xcrf4brsKPBZnbL+7ucWB3d1ec84bvD1xTHBsXBuCblS7f6uABsyD5R1xfC5z3X6R9TLeIfQQfnbwy9Q/UTwSZ4du6BBrEDYcyIS2IGOMvRuHV44UYI9frFXlYqb2TTysaxOZviOMa8yl9BXQMIY8xIimhcwJ9G9aYcOGZSmSKwqOA1GIjC+uOjubAo6LYCMMQgqVpWAY1aMwZLpHo8325pal+at1KPI+sQcjrmTnuALBT6xaaj6FUsyuTsgclMel7H91oKkt2DMK0QYeFoto4xjEM0wohkJfFcZ5OzJHRCiF5C7oVc0UXQfrOaFeEbuxWwfUsppEZW/P2sZjD2R1GYWpiwxDMq1bvfn9bQctigrLWGt3XQh1Gyb8/wLrcBYCvH1R369EyWMco7nCTOZd2LtkhH95nZhP3a1y/tt7vr/vgMx8rRSEdlomBD55R5myYb3Z964PHT6ov/1GXfu3v84z8IPxzMw4TMOct/5cEE6CNGNAYibIQ44qEBTCm4Pm8siyrBQD8JBGhtGr1vConn0Ifp2Vgb8doSAnWvRkSwQNITJGgDd0su+gqLHm11LKUG2PUT8qOM0l1ID7fBNJNNKdK9M7Q9eWJ8+nE4VAVvZWMScLnx2J4jzmPB8xYCc8yJJibm/HG5MArzHrQl6S7lqeUiL5jVDvIIEYLgjqatUl1ivPs86uloN2Mjtu1mdERneC24Rqj2xt6EGqmXYmn1Sn5QuvNadjB1L8uJpvK5LkR+/BhVSGgrR/6Jkvz4ZJtGuFTKXz1cuW5dTZ1x7Sfsth+2uqcgYCjZABUj5LnPps54jq3Qw+1A/RWnP/05xp3v5gZ6gwaMdjYyeP+gmcfPynk/XzXn4Lg8fMEjZ/+Acjd34JqP8QzAAAgAElEQVTcYR4z8/AbDTC3rZggLEhcsPGJybMJc9yKIRGjScHPD4+kdYGQ6ANa6eQlsJ7sZ2bxF29U6WFakINgBdZtiHYiaHOr/2UlpdVGQqoiS0ayDXVKKbu2pNopNMTp04bGB+YMm50oUFshjkorZmsQRkfGQh+LkagkuIhuIbRBa+Z5qgLai5ccxhYV7VaKeG9bFCS5vSDWJpwjDjWIAbYqxLDC6IcqVYJnetiCDymSVitXQnQa+Ojo2O07CYO4rDbewo9kSRntBUY11Wuv6NidJ9GN8RoCvU7sShCJ7P4a6zCRoPpEe8Rc4Kc5z/Rj3fZCK2riYJFDCWEH0893oIWf+NMb5jILSBHbkJYFy1GviAsRzaH09vw//og//rzJwXcRV3rLXfBQvBT9ZtefguDx81y3j21+CVZH+1yXZI5KixhpZ8qZzb3Jab0OrEmIkDIhrhAyIWZyVC6nxJKzeyNETqczi8vsX15e+Pi0UEs1r4Q5NV5vng3RS5gJTLbWSJKP2jN4Wh6WE+H04KeIGTabH4DX+N79qL07Pd1HUNZCkn54dhBWY1PHCPKASETrC0F3Nxw2f8vhm4/aQZKTk9QyhDBZvCaCS9nHMuDpfruNpJzZynSqGl4mHRhPH+YA5ic/QY4sydy3BJFhnSeNroqNhMsDul/RdWXs3Xw+UOOULInRNuO06EJIkdgb7d17eqn0Uux9xeAdq+C8mAG9Havmhm9ZNhYk0LSTYjShY9qIXX+qcc4tK/i6O+mt6pCv3f7+9wET0kmwkRZTE3WUlZ6tVaPbHIXGzwxd83t2bc+hlfKMBGDoTw5tP8/1KxE87gPFkgJ5sj1TYs3WYrWRBpbO99bYy6C4VeFeGrWPm29FXo2ZGVckZk6L8PoxsS7WKcnZnJlerlc0RS6nTK+NHgJNbSxmch+QpjaO4eCVTGBULIjFxVqcQdVmluQVJRDwbkHDGKcScSExg0rMq4N9gqjNfNXWjlUaU8YsvmzxoZih8GhMdbKxGxOIDck2vkv3GS+DIG5GRPEWn/MjYjpO6zkLpnch5QXuPCju2atz/KUBd+NgsMYc6WPY6xWn1odAd91HKM0+zwYhJsvGYrT34acqo9t7rxVt1WwfxY2ys+s93EhnouJzYxrUddv0qibqe//yTBDhux9/zA/e7ygmvZ+ETMW/Cw8ozX/6NYjC3v9P+fcsTwJCEjPvIdsI1DC1W0OJQ5De/cDrxxNEsWz6mFMc/H3M30dzrluWxV3sb0TCeelPyYt+nutPb/AwbI8UA3nJrMtCzgvnJXNeM2tOrEvitFq2YNPfPKVv3QdD7Ty/bMS9cN06vUdCPEFYIZ0gZmLMPKyR8xrIsfLwsHK5XGitse87YV3Iry8oRmwyNWqf+bj7pbriM0Y3xRFUVrPlcwZol0CMizNPg9n+TX6A2MbufRCC+uK62Rnq6A4aZupuqmEBxwmUJL7BFCStmKmHnf4MGL2Ql7OnxAIaCSG7k5i5sttmE8/cFHCbgQN/nWCotYBbbaS8us2g8ShGyLS92uOJt6m7k62G8Sy6AK0T1rN5tQ7I50cHFM0Yem4Q47okwsCUuTGjrd4CW3SpfjcLx5khHIEDo/ET1DMRQ0AVobbGVpXXpxPfefWaP2ajbPutLa7esZsBxDMCD5fc3GfsAwp3f2Z2bNpHIcVETF7uJTOonrfToXSdkw4b2fGlEG2w2JIiS0qkaEF3Mqp1GCCa8uqB2awT7N7jlnmM/z+VLZ5yxWS6lNOaOa8n1nXldDrxcF65rLcAkpbkjlfBTHdcY1BqJV9nN2BDx06rNlNDY7aFGDNpWcjJTt2YIutpNWpvM8VjEdj3HR4fXcGovHnzhs8eH82XYqL5cGfW4u7eWBYUYnIm6VxqDl8ek92GlRFG0KDXjb69uCIWYl5cXGd/j/NkyW4YXYq/T88U1MlnI1hdHOxECyl7smAEtBDlMBBi2OcesBR4bqDhDNHZwQBgmDZFxebi9G7doaDDdS2WYfSuvlkV8bLgAJXVxIfQofnQ6d7RsUDKkMzUl303E19V7z6BLCY3D11oEzdwkto0iZIwOSrdNv/R3pi0AOHd85WrBtJyYjlBc+Mfdap7dBOeoCanb96gOr4LOAKI2+SSxOwgkkx/XLNsTMlsCHpMZqo0xN3p1WbmOBM5pkiOkSXbuj/nlfNqZtvm9G/BcXS7r7oNpVWmSnM3vZn9tl9VA2S41WYync/FOhhrWlmXxPm08up84XIx8tbllHk4ZS7r4oOk483qb7Sb0KgMYsh28owAFbaO6UhSQmM6PB9DFGKEh4cVETkUkWMMHtfFFrFCq4395conj2cTL7WG5mzsU8zhPUXTsyg4fH8j+jAzBqaAS3z+bjWvz9EOWzwzUjYPUwsKrs4Vbuedip3IyaXoIuiwTRPE8BId7tPhi0xkllTNRkyEgGhmGhPWoa4juWlE8NOuDzPX0TaID2dqF/CBz0ggaHd7xGj0cTHA1n0iid1LHSeizTbyKNU6OjEw9g3dzOdU1oiOBrWhZSeqZXwBMawHa403LZaF3Pt8znUl7v/hmdUYw4HGSBuB6xDW0wMPQ+itUrWgOsV1zTCcPp3TDvWB4Rio2TY4+S4EJQXhFALnEIhBD9Znyta6JyZGdOWrDop2wrCATTfsZl0WHtcTj6czl8uJ85JZl+RMZS/Nu8kwVAJ9QK2d0jpbbdR+C6Q/kT/yc17f+uARU3D7OvHxCJbmrcvCaV15vJx5dX7g4Xzhcj5zOWceLusRPJJPVEfN9n9KnK/XApiIrNdOW8warg9r9Zl1ekSSe4YGxwe4eUKYIfFw639hL7s/j3oXw+v5ED0YBAc8HaBzkNGVJrbp7QU4NqDg5swxmBdnUKwLdGQl4tjCQHIyHYsCPrFdxH1IuxLFuiDHehGxTo+L44rPNQlq2cBoc4RBQCfb9egcWb9BxnDtjP0vuC3kGA0Jma6REK0sqXsBFE0+rc8nySGDVl1+j5VyxGAlHmptX6DsO3FJ5pg2Z8RgVPCRh/FcQqKWzVu0g5SCCSdHp2ui18qhIJ4bXSydn+zPfnShIoHMKV/oqpR9g9qODEWPLApUrd1rr8k7HcFElymIjQeSQI7CJQVOAQfwfUiUO7HpkhghUUmE1mEEmkafV2NSh3lgvrqceXg4cz4tlmU7/2Y4blO6refSBqWYzkWlMErBHNz41Q0eIpCy+WbEmFzYY52LZU1cziceHh54uDxa9nE68/B44nzOPJ5XTh48AtaSa624HDowhqVsa66c0sKeKpu3rZJ60hluJjIxJUTsddS6o2NwWhen+Ap7LaDGL0g8EmJCxWrnkE27IiEcIxEVdcDLNv9oFXFOiHKjj1ttbLocO1ED00zXuB02RDqo6VLUT2+XZXk9fnObV+d3iGLeHyFgNkDm0Rny2ZSsBbKjINZetvIliBh3JpgYL0qgbfsBxI2haDBuikalk+1JFWI+WaDAhXDdWqBtVAMthwnHrDyzbhJq/iuIoD0wXiqqmw3NjiCjo73Tyoud7utiFPt9Q8sgiRjQGq2rFkbw0ZoTJDV/VmOgWgDsqmy1EkVYU6afzvTQyc+ZnpIFa1WGGEnNvFW5+cgOL0+Ck7RCIBPICIsolxS5RFhlspCtC0RKaM60EKhuPzmaaYM0CAE7wB7PFx4f/M/jhctpYUmRFKNP+cOk/7XShlDb4Bo7hGItZx8o1bs5i33T61sePIRlNet4CyDxEKmt68rFy5XL5cL5fOHhfOF8Xni4LFzOK+uSTZwGjOau393EdjEqIdTDIj9Fm7BV1f0nPVMIWG/f2mk3ZDrnzPl8JmefxaKGaaBKlMDT8zNlu7KGxPrx4m3VaODdBCCHM1EFcwcbZhWg3RioR4cAxZSZlobGmBGxjsNoO60Zk3J0cyuTEG1Y0wQ3VXwj47NTu6tZrdSSoGCznNAGumYCxebE4j4gIt68EUjBgNC4WhYxcE6HgZhBA2NvyBKQuNA0EcbupZOVV61XZHRi9FjYleTA8FBj8ua8eFnQ7PvPEZYEdPatEETJqw1XSnHx8qyZHEDNkV1790oogVqp2twY+eYc7+WLzizCgkCMkSSJfFrpWvzfDhS7M5sGm0fTYjM+kFr3I4VACrDEwCJClkhWOEXhIQivQ2Tx8RlBxHVKplVqIbAhVAY5CGNYydVUyUvmdD7z8HDh8eHBypZ14bRkn1Bo9LJ9T+RSqU0prSNSPbB1SmuH74f8EqnHtzp4IMKyZLIPrZkq1ZQS5/XE6XzidLr9d1kWlmxdlxgzwedmWDoqBryFiA0kuhvXoEJQcftAPXr+uPFLQO35Tmcrn1DWJZNiZF0XSi3EyyvKfiVH4en6ghT4eD3RgztpSWBgRsfdnc+GOicDk4ebm5hbKqqzAoEhid4qMQekB2ptIBV1gxwzNcY7Shz0795sQ8RgNoZjKNq761iGg6JQy07wjdT6lXi6MJo5deOcDCV49wVGrUb6imcGNou3bRWRQFoXpFVsHIv5dRAzTXf3GLHu0KgWOHrpECGHSB9KK40YzW0coov2bNGLt2WHVispxbIEHRDPr2yg9PXJvTNAumEOJrZ31MbJYpa1yaFWlRhJ0yVM3RMkQo6ZsKyUtluJGSbBUExC4F0ixT1k1cY0pBTIwYLIKoHFM49TsODxmCKrz0yxwVrWph0pUv3nRYStd5JFN0RgWawcX9cT5/OZy/nM2RsEF+8sjjHIaSPFnb3acHh7r8peKzkl9p/Qtv1Fr2918BARcsqsyYxVYjQALyYbqrQkCxQpZ0IKPpk9oiSaBwSabdLeO1u1P9fW2Uqj1kFvZkMfNLHoVK0OgqgZ6oXAeVUezyvr6WJpdR68ulzIKfKwLuZ76kzF05KoKFIr+eOPOJ0fDvdqH4Rq7dHWbZCSv09FvX4ehrrrzYdDVBG3w5vjFq0blBi9uzthJySMpco8TQe9th8DZZuOQxrfVdBopCkJSg8gxU9rR0dUh3eqBA3BuieqhJgR8cAQEkOFFhIpdFqApJFRdzif6SMQNSC9o23QQ0KWE7QN1UrtSi+V6I5YIS7UZrR2ew1KrYPTOdlr9dEH2rvhWq2hdBtdEQO429bRYUEMS2rWFerO+B0OTlsppyRVWhs0HUQC5/OFKrau8K6KaPfW9CTIcRw+criqiXeLbURpDoEVWMWykTUnTvhQahEkBXoUGysarGuXFbIO+lSWByElIefIuq4WQFbLsh/OK+dTJueMqrJkmwYY90LYoI9MGZ1YAjlAlBv29k2vb3nwgCU58Sv64JpgSs7oWERwyu0QEyp1VWozenXtRnbSYbNASqls153tunPdihka184E+VVnzmEkquAndoyBZVnJy4KMgCxzBq34WL9ArZUsVrfvpZDFFm3O6UiH54ICfDNPFqGVFrdLYbqnq0Kr9FbcUHlmTbZwx1AvyVxUNzqtVYYKeVkgJsp+Be3mGK5YKxDDG8Ywj42mA+ndmKsYWDxk0F52YBB0ytlNMdxqIwx8qLW1GYMO6r5b/a+JUQXtO61ubiQ8TB3bYYRAHdaiZahhQyr0auK6EJPZTh7GTNBrp/ZCyoJoP0yrX16uLMsgL8nKoW5dHcXe1zR4/tAA6tbJm52j4AdTXIwEd17PcDqjkg5SWNC5OrxTBkT3NjXyPc6Hwf/Y2s0iLCKsIizRgNNVzEQbse91RGvVIvbZpACJSBiGj2n4cApczollXTidTpxPK6fT4utN7/xxhT6E1NTm1sb0S2Ub99e3O3gAOZqtfo6miRAPIHDXkuqN0KbS0zQKsVtU7WOYfVvrtL16m3Wn7JW9NEobtKbuK2xMyMMTwbsQ3V2XZksveE08VHl5fuH1qwfePz3x6pR4/fDKN7OZHQ/vfty3xaYR7wfjI5hBRA30tB8dmEVYVnMYdz5Vc9q7YABYLY2uRmSSAcQV9QC2lR3RQWgVG3t4srYlFnCilzm0ijalhZ0RhBhNn1L2jWki01ojnkzLQ+ukYDNSRhiEWtHe2Yd5nwwRlIX6/h3x/EABe94+QDoxGWlMRrPNMZQxBG3u1i5Wxk0Tp5QitVWadut6MFBM1VvrC/19JYbBKDunFFlzoGOPM4aSMCr/NA9WF/1No2cwnGiNGVW41oKUHTkth8ub0cp8naAHp2Mu2IAdZhaMxIZNz47LBFGDcUCy+MxYq2u94xNQiexhEL3tHKObUPtBNQHWGG2MZM6Z5NIJGyGq9Dg7Wrf3dwyJv4sdH67BX+z6pYOHiETgfwX+SFX/koj8WeD3gM+Avw38m6paRGQF/hvgnwO+BP6Kqv79n/HYuB4cDeokmImTV9oo7C0Ta0SI6LBUrQwIzVqGvXXa6NTW6HuhlZ1Wd5u3UTulmLN18zmmh8ku3InnrEXWtSGj+6zPyPXlGRTW2un7zuevH1A1MtFCoOw7l/MJYdK5wwcnYKcjTt6ytHnYBg7mvUFcrJsYg2k6nBGqvdC391xfrtSuvFx3yr7TywvaB+uyEi8XQo029+PpmYASki3SkJJ1WnpnlI0coI/Gw3omIJSnnd4HOUa0m/bFvEAGGga9mKxlTcmsCMRZmgTLRNS8NiWe3EG90HfrJKEYT6IDewdZGdFVx5hD2nQAJ7m3x1BiSJQ+KKUQsKFYz88v7KUQgmV4rRVyAkYnBzit8LAmFsHAcoHWq3dFPMO8c9eaV1QrnV72Tlw76eQ+JIJbGxgbR9HD7nHK68MxPkOIAbIEcjD8YwoCk0SzWfDggZdMVl6ZE68E9XIoEDA18xB113fTaMUU3Urx1vIVxzamb8h8tWb05uM1bHXbM/8JYx7/DvB/Aq/93/8J8J+q6u+JyH8F/NvAf+n//UpVf0dE/qrf7q/8rAfX23u9+5nxK4YOai3sMTNGpXUhdaE0/xLVDGRLb9RW6Xuh153RCm3v9NKppdLbFD07vqA3Cz0dwsPFRkj21uzUCIF3797RaiGlxNu3b8kBSq2sKbAsCw/ryrIs9DGotZHT6WgP3lvBjTHsRAlzo1hL1Ba1vX+Z7NOhvDy9Y395z9PbN7z96ivevHvPdTe7PRlKXhfaGJwuZ2qtPD098ebtW1orbNdnUgyc1hN12wmqfPR45p/4/vfRMXjLV0a9r5WcFhg2/iTChwOR24LGQOydlLJhNcO0QaPs5Bio+05Yos0a6QrRspvDU20oWitgnZfeK6oNUSGq0kejVYzk1Du9X6l1Y7RqWVIIVo4x2LYrXbsRCS0t47wmHk7w6Tny+rSwrheSK2Vva+iu7p8AIhxZxhhKdk9aSx+5rZO5LH8C6Djdu4KYpaQEcbEb1plSO5DQyefha495/8cfy5R9xgnxLOIoYbwL+YFmxUHd+Trk/vHn6w7hwLW+yfVLBQ8R+U3gXwH+Y+DfFXv1/wLwr/tN/mvgP8SCx7/qfwf474H/QkREf2bepMd/jrYl3Bm4NqQ0hia6dorPVRHh8HPYfdJW33ZzDe8dSqPXzmhuVectNuNTqIvDOjksPJzzZP4yhnLdNlqth6rWdBzpqJlnYGitsaqJ8uYimDhH8BrZP0fvvkzKt2UevfXD7q+PQS+FWnZaaXz55h3/8Ku3/N9/+Id8+dVbQky8vLzQWuNyudAH7NvGy/XKteyEAOeUWEPgcj7z6cefQB/U94Xf/9//Dz57fCCn5EQ4+LXPPjeHch2c14XFh2/lnCFVwuVEbpWQVlrdiWMQYkaXbgZBaaHsL2ylEtJimzNFE7yNjnaX36PWWQnKu5dnVndeqzES1oUvvvyCd+/e2XyS3hltI0VorfNSdp7Lxna9cllX1ii0arYFlzUz6jOfX05879Mzj4+Fy5KtqzM7ahPzgNspdYdLia8zmc7kk4Anfh9fY/j3ZvDMtCaU4zuPIXrGoB4w9NjJH+Awd/XPDBwhWJnUPcpMg+ljkPXdMOtpZD0fb7abzZDZ2vkxzpInmvx/3DRSv+j1y2Ye/xnw7wOv/N+fAW9UdRqA/SHwG/733wD+AEBVm4i89dt/cf+AIvLXgL8GWK2H0Z5Fp2v3Lcra2MhpcGLU6UB3g5tg7NHRqG3S0o1FyuhI9xmkPkLRvjv3VVKQPqBXc6gandPpRO2Vsr/QdLBki/pzLORAeSmV05J5ta4s2f6cTsYFkaBH7Y7YCTKGQFgY6r6g2g8zs+GB0oRgWNAbZr//+3/0A56vBR2Rx/MreoMf/PCHLDHy+vLIl++e6Tnx9LKx7TtffPkjUrQuxeVy5pOPoGXTAX1yOvGwLPzx+/eMdkW1W32eVx7XlZeX95zKwquTZyQ5s6wrj5eTTYprNlZSJdAx5W7bG/RGikAv1C7k5UKtG1oLUaJPbVcb+Rjh7fsnnrfCcxwspwtPW+X3/+7f4/npPUMH75+eDfCulmX96P0LWykMBpfLQt1eOKfIaYl8+voVr06JV6fED//BF2ztNa+fMp+/PrOmyKvTYgDzdC/nlolYyzuaUdHEpvbinS/vijHNj/T49ywD7FvTgxc0T/YZF1RAdAK2uGmPMJs3Zn5tGz+EcDgQid4Ii0GM6i5hzjg264jg/rdo96wk07t1acLdaI4QDYsZqox0l1H+gtc3Dh4i8peAH6rq3xaRv/iNX8HXLlX9m8DfBFjXrNFrvBQjMUUfXGMn5LpezJgnmLBMJTK6lTQWOOwUHz6Fa3gqivr8EMsEp3KcSQcRlcNDg+G+Fwp7Kegw4s7R7ehGPx/a+er9ex7XzOOnn/Hq4YH1tNqmxXkKvoIGSkwLARuhaIbN3SnfJqVuYyDJFmMvO8/v3/Hy9I7/6/f/gH2rfPnFVxAC11p42Tc+/exTlpR599Ub3m9Xnt5sIPDu3TuWnKm1OXjaeNl2ePuGNh7JOROA04PNn3l+fo+2wg+//BHrr3+PMqBcN1MMt8pZAvlsXa0YjCwW8DUeBA0Zya5haYV1SXz55j0tWP2jw8dY0olRuJaNl+sLTy8bQwI/eveeN+9+wPO28/7pPdeysddCqY2v3j3z9mWjS0R647IuaG9WTkahiHCShZeXwr5tPKVAAv6frzauRXn3Uvjep48sQVgMBDgyhyOVF7NZPOd46FxqLQ5iy5EhzPziqGZmAHGCoXjJcmz4YLqhMD8sONrD9y3TqfjV4/E4OkMz45gZSYjWbg8xEZPxmozaKKSYnZXd3djovjbytm8QevyTkeT/88BfFpF/GThhmMd/DnwsIsmzj98E/shv/0fAbwF/KCIJ+AgDTn/qFYLweDmx5oW0JFLOxLiQYianxJJPxLT4jReURPEpXmMIdGNlHjVixAYnqwFfwam8KuOoaS2m+PRy13KUaotREGLK7NsL65LY950lJB4fHihtp2ljWa2lu15OpCV/0IE1OvCcIubB565qm+I1y7DcI7Q12vZCu77w8vYtQZWnlxfePD/xo3dvWc8XfvTVW2Pdnk/84Iuv2FqlDwMd13U96t9aK6fzhapCU+FaKj/44guWmDmvK6V1vvv5d3j7oy94PJ/YW2c5PTBG5bkUznmxIdPO+A3WrqF7VyAlm7WS0kLZNhtPOQYSBm+++iHnjz898B5Vs0fcy8Yf/+gr3j+/sJXGc+u8fXrmZas8XZ95+/yersreOs/PO+fzmdAGI8JWnW+SEy/bRs8mgryiLOvCF++e+K3PHnm3bbR2hRx5rhsv24XvvrrwuK6oduiDHOLxncQgPKwrOe4GVqdI7Zbqa7QxFjNwHJiHZ4zzuvfOuN/wNkvnDoOQm1P/vB+T9RrEiXUfljkhyAGcfthNCd4q5ujKHBPyHES5fz1/YiQxVf0bwN/wF/YXgX9PVf8NEfnvgH8N67j8W8D/4Hf5H/3f/4v//n/6WXhHDJHXj4+sORNzPrKOnDJLzuS8Ou0YE4qRKEPYaqc0NbWlzjrQvuzmg5ZBD1Ng+0AjUb0PiqJ00AokVGE9n2mj8PL0nn3bSNHmpy7nBALPLy/EqMaGzelgp/pn5e9ImIKroQJmwWPliHto2jq011XLxl4qb778gq++/IJerfTqtVF743q9AsKnH31s4wGG8ur1R9SvviQApTXrzgwoeyEEYXu5kteFN/sL72Pg1atXnE8rYFT103oi5xOtDPJlca7CgunyFZaF4N+FqAv5UOKy+ggFay33roap1J1Sd1rrvHnzFefLK1KwifXvnt6zl50v376jDuXpZef9Xthao4zBtTZag7isZFHOD4lSjI6/b4UUhPPJ2MSNQmmDNy8brTd4+2zjROPGOQc+f1z4+LQwGlx35a3sDIWLY1TRZ54Esfmy5yWzpI5ms2bIrbMumd4S2tVm4nJT0TLZH2J/C3ebU6aRtk/kE9Hb7x3Lm0WRuf/PcmZmHOBWd+CA+3F/VzXPrCcEccuBW2CY+N88IFU/iHI/z3b/idc/Dp7HfwD8noj8R8D/Bvwt//nfAv5bEfm7wI+Av/qzHiiGwOvzg5FhlpPTzqMTZG4mPzoCEhIdYekWCJDuQJgBlzEqrbu0eeD0ZJi5xuGm7SmjioI2giivX7821ue2sZWd2irvn595vFwIKfJ0feZlL1yWQHHnK+CwApjPY4spGJVZAK3kkBExAd0Ygxyz4Tyts72854svvuDdu/e8efOOGDJfPb8QYuTXP/mU77z+iN47Dw8PpJz50Zs3fPXmDY/JMIQv379n3yvnxzMP44wgxpNohU8/+ZjHyxnVwOPDmTUnHs6PJAl8dDmTVRmlcX44E5KhQZPMltNiQRult4oKnPKjg4GVuls3pPZKrTtb2dmaULcnhsK6nhmjs5ed989PXPdCU+OuLOuJRuH5+o6zK6Ov/y95b/YkW3ad9/32eIacarhjjwApDuIcsk3Loh0hK6RQKMKP9h/h/1EPilA4qCAph0yIIEEAjQYb3Xeqe2vI4Ux78MPaJzNvA5BEwA9N+ATQ3VWVlVmZZ++11/rWt75vmMihCCwl8MZRLTxKZfrhwOt3BxZ1zcI3hX/TM0wDWU5apZsAACAASURBVGVePQwsvZYgvOt5uqmxRnG5XnJ36Ei+pnJCHdcFZ/BOS2ZrLRNAkQb0zhK9IU1CiyeVNiqyyU+B4xww1aeBzkLemsFMpSltcFDleaTsKEOTzFFE8A2KBu+8jo5doLm8oaxdXWac8zy/c1a1FPpDPgtav+j1/0nwyDn/O+Dflf/+DPjjn/GYHvg//j7Pa7Ri0VT4ygsA6asSNN6ftE2xzF6gGQJkFUnzrEEq/rFFyctaR5yK3N3M41BlnLrMhkj7RfCPeeht+/DAFAe6riMMPaquj8Fr7HuMEhbqrusYp+mnbknOSQhapcsiUnnvk3RmO4OcMl134ObmRlrRw0hVVYQpS7sRsMahXMV6vcZ7xziOtLXj6dWGoe+JQ6AfJvbTxN1+Rz8O0jFAhvG81dTO4YxFk1kvF1TW09Q1zmpq61DFc9ZZwZNmOce6boBISgOZjLP10R+FMJGnQIyJw0H+jq4beehlHiVqTUgJYyxjSDxs+zLhHEtA0tTOYy4viTGw3x+YxkjMEW8svrWEKTCOIpdYuZpJCVs4hoyzGp0Tq3Yh/sLO0diMN5lEZDcGXu8OXCxrNnXFhCb2E8Yr6iLtKPcKjNMMKUqpMU++lnJNZyAkQjyiFRQw5JRtSFSRe6s0RoNOSaZ/oWQZc4tYH9eMZBb6KDegy9f5WHIUsehSeovu7FyKnOEpZ2XJvMzmKevjuvvFY8c3m2GqtWbZNjLw5quyeN0x65inbGNUwv9XGjNlEoGQFCEmkRYM8uFao4jGiA5DmmtADWZO5/KxLpzVosI0cXd3x6P6ku5woOs6jMrHidcQAilGWawmy9yIMSf8ZH6+EuNnYNEYc3TwEvd6IUdZaxnDxIuvXjBOwoaNMTD00mVYtQva5RJjLHVTU1XiXhemif32gRFLnjK5NTS1x/dyiicj1oIyNOWpi5CSnYNHW1NZyexcZXHKYCtPSgHrNFpLtlfVVeFBJLp+j3dNcb4rAneiNCSSAsYTsgSG+90WbR1VzISUcM7TD4GMwXkj9yyWTkbOkmnERGU9emHoXaBJ4r0yDD3LSrpXxkhWlJI8niQTybbQtJXSoESOAQe7IRFRvGoGHIZcJa6ampiKN0whaDlnZLNrYaXaXBzxJitB0mgR6TmLHbJh3wcgZxKX0rqoiSl0yscMYyaHnWMS5zjKeelTolHJPoohV+GhzN2ZU0n0/l46ZhhnlIA8W5X+gtc3PngsmqZMEs4ZiMM6AU1nMGiKWRaeUPIISTEGxWASSk/FmU1jpojVkWgtKjvICmUyxEmGw5QYMZOlwaYj5BAJY2LsRsZ+YBoGJhKLusEbTyz1b86ZQxfoxsBhmgqrFbLRQrhCJnhzzHhTgLOSEQnKIRtgf5g49B390GGVLtOnnsWqpm4bGt9ii5ucLZ+LVYax7/BkCT7jwLu7G/b7HavG8u0n19JZUoqYMlMJfLkwcJ13ohlSMB+TNb4SkysjBTPWGpkk1sIDTVleS1lhvhojNX8KMKWRoBN4R38/0o8d+64j5p5lVAyTGGrHKPNHhy6cBtjKab2qmsKbkXbpdr+nDxMpBHLtZNZJKRFSzqL3KvtIMwwDMU1kMt040neBbCBojckSHB4OE4c2sGxbdmNg4SxKW0zOOKWpNBADxmVcJV4+zlmU89LFi0FsDWbZBuTvLuialBllkmIGLlVOx5IFKB4zp26NUunILAVRmxcMrgQIzLFckWxlZo+eSIamBBitTqDoMbCfKamlkpHH9IunHt/w4KFYtHVJlWWK8Jh1aMvsQepyZphigR8TY8hYW4yGjMEYmapMKQs120zkoIrMf0IVPa85PaXMMMwnwTRO7Pf7UuVotFEslysOfYdSmdoatvsdwzSxXtWQIU5BypJiYyAnmrQ2wzgWC4MyM5PFjHrOfLQ2GG+Zhglf1Sgcrm1p10tsAXt90xwX6zh0HA47slV0cWIII2NWBGXZH/b0w3hcOEqpU9dHKXIOjJ2Q6HTWVFVNUQzFWFFym0fVZ2KeqLvJeLgr5lZzZyrnQM6RaRqI08gQ4TDK1HE/BELcFcX0yDhGwpQYA0CmKlq0VSXlqdYwTmIyvV7UrPAnrdN5c2iFd6p0yGTKNgZhrE4xcLvtOdhIP/akOGG1I0dFP2bGKRBz5s1uz9Jr1lUFxoISacbMKUs0KRbrCbGfsMbI4OXZdeyYnHViZB3ro47unGkwJxLz484zj/Ic5X/ynD8jM5ntQGcMRBVZh693eZRSx65eLDq+88Rx+Np7+Ptc3+zgoRSVkzKl9hWVqyRwFMzjOCOSJCmbQsZajbXiRnbertKZItmf0NYQQ4n5RqNn1Ycyqp7nm3ZU9RLQtW4c6/UFTVMRUub24RbvLblQwUPKHLqOh/t71lrjFzVEjXJiMyAtNC/mPSVrEswmManIdn/g0A9sDwfu7t5x9/Ydm+Waq/UVeoDuPoga2iianFMIWG0x5aTxTUNMiRAS3omPzKJZsGhqUhSAMsRI5ESOIkrQCuPERGZKA/teOjPOGdq2ZrlosJVhtreY1ack9Y3iJ6MUaRxR48i02/Pw9oYUA4cxchgCIcFhGNl3YxH2TYQpkZLC+kqElWpP3dRHejhkKm+pKhkzN9oQx0k2oMrHx4Q0UM2+PBhCkKymRqN1ZDXVRBaoHKUlG3uaKrHtA/V2wGnDNCSZSbKu4BP6CHhbawkpYk0R7AmGeNy0p/L02HJV82bn2Io9lg0lTsyU8eNnWT5D+RV9zCyYW7OlHDzFGXXENeb2v9g1nAYm4azsgWO5Es6CR/xVDR5KKbyzGGdlQtCIm/x5xJUIf04tlzkCawy28P+1TjJToEHrhDWOaIrjWuF0GLRoZep07JUrpUhoMX5yFdYoQop0U+Dh3QPj0FM5GcfXSmGd5dD1dPs947Kl6yK5tPaMc2QUOo4450TYOEZU5Uk5MUwRrQzGeLbbGx7uO5bNBQbDOHYMY3ccxa6cxXlPvV6zaBdiooQI8Y5TzyGO5DFQGY23NYfuIHR7kL5tCkXy35B1ZhwDRluR7FMyJCdDtjMOYXDOo3Oi8oZkFM5VeN9QrJ5AJXAGnS3Ltkb3La/fviWNHd4YpjHQjyPjMDLFMqgYoaobLjdrqmWLqSvqxYK2aUrNHwnjIEZIRiQco7JFtSwRUiCmgFGGfkr0cYTYE0PCGkvbepqF4e7VA3d9zzgFrIKLWnOxXHN1tebJoxVP/tGHPLx4wfRwj1JgbcZbyWby2KGiqNDpolVb9KMKOKlK0ckpWBQSh6KM8M/MVcrCShL8ZtbxvNayLp0SlVFaMmEZoJv1ZWIpbUoA0XLs6fI64oioiUrMy04cjwykwqbO5bPLxYbkv+oG/XOvb3bwQMSORf0LOI/mzGnhqcc997/n4SFTIvJ8Cmg1DxYZtLZEVWTYjKDdaIqeZTmZdendZ8UwBLQW8G932BNSIEQZzDv0A9Zo1k3Dwnhe3tyxqivcskJ7Wew+tijrSDofuypaZbFt0IoUcxFm7rlYblg3a9CKECY84l5mrRDlFIq6rvB1JX9zhmmYiCHR7be8vXlNFzJvb+8ZpsjDfsuh39P3PVMIKG1oqppFXbOuPL52VLUohscQiGFixh/DOBwpuOpiSRMTOUHVeHzToFMmThM5RazW6LpCG2jSSGMDr29FBq/ZWoZQMYyBw9gzTBPL5YbN1SPGmPAxsakqvHOY0tnIQVi5GRFIHvqJfd+x3e0K0pCLWJBMRFc2U/kK7WEKE4cxYnPgw0ct/i7zk3eBfZDJWm+3pDgSwp5d7nl8+ZiDGVkkhUH8UFpX0Y8j/WFHdjWy2k7NzRmvKpHkWFacio3CGCoYQ4QiYlS0VASlP/6OKgJWJRzLZ67Ks2TBPk7zXepYXh/LlvmVz9DSIwmstHlnCn4uv/9LNFu+2cEDztK/n/H9cxLMOSo9Zx7H8WUjgioxpuPjjNHkoCWSK4XouahSvxcRnpKW5gw52SJvl05oNZmoDLt+JMSR7e7A3XbHzf6Bd/stn16teL7ZsFmtWK6TSCXa6qQdqWSRp5zp+pFDPzJMibvdnqpu8MaSQ8LVFXVdFeJh6dQoS0To3v1+z/5hy+ubt9zuO/A1gcxOKbqc2WtDpx27ONANEZUj4W7PNIxYA0+vNnz85Jp144WjkIGYSJOUFzGOJJ2oao8bNd4ZtoeeZrkkG1Enz8NEnALGGsgBbxK60Uy95qFVNF5zu40MU2BIGZxneXnJ69s7Fos1G+1I01SYqRmtDWN3YLfbsus7tocD/TAW3oRFZzA5U1vNutF8+nTJ06sFfd/x5bs7vnx9g8GzbCtsHPngcsntds+un1A60w2BlFsedj0q3FA9HLif4D+N8EfPLmm0x+lETgP9YYtfuCIvUABupY72jQCz1sc8Bj9/LyUphwLFm62c+kEVRQJ5ZOGBQEQyB5gPRo7AKMf1fkJXznGQ9/fM179/FtTmzOjrLZm/5/WNDh4/Lyqev2ldWq06F83iXLKHuc2mZ2cuLZoM5VSLxqKNmBHNjFNUOhoBz3Wi0QpX1aIwpQPLVrHfbxn7nqyKCXTKTDkz7Dtud3v+7s1b/vy738cZzaptWC8aLjcLHm3WPF2vuL684mKz5mq9xmtN4w2X6w2LxZLu7o6UI11/QFU1y8UCrQxdP+CcwlpPzDCliBpGDt2BH37/Mx52HfXVI+zVNYcQ+MmLl/ztZ59x/7DlcOgIxa5QkVk1NaumxdaeHCZevr3jfnvgo0cbHl+ucUqLwlfxop3GzP4wsgqZpJE26+GBHBdotwSlCOMEIYrfKhFtRAmrdYqVz1gd2Hd79uPAGBMfPH3OFJIwNGNk6DoOKpGnyH63pxt63t4+8LDdob1juV7iG0sqws4xBTRKPHGNZpgmhqGn8Ybferbmcav5/pfv+PL1GyrfkIh8cLHgobsXlzkjLfFFLbyhytTUYeJ7X97wgzc9/8PHj6hrRxsSDyEUKwc5mFLhXMhQ3NwGLX2WBLlY3KesCBlshlBa9zmBjomx4BOSVYBxQiKj4EH5GFaQGZx4wkrIRfFdS6muSgmlzfzCp+RjVqw7zUmoMnpxWva/6PWNDh7qa//+mT8/Q6wlDszuXBltpJcuugqKeI5C66IynnNpzZoixCI3hXQKNDklxmGgqUWhetl4vBF84OmjR2itebvdcvPuLfeHPUZ5+hDZ7fdsu5E+JN48HPj+FzcyCakNaE3TXrBYNsSHN/yf/9u/4dnlBSOJDz58yrA74JuFeOcmsQGwxqGMwVlLThMvv/qK//zd7zEow/rRE3789h2fv3jBj796wd3dli4E+r4XZTNm9ffMtht48tjjTGKpjQyYjSNfvLmhmyauFi2NsXhtMEr0Pr2xVFV95K/UdcXYdXizJkwi+ptIZCXCPCoZUrIslg3XceJ6sSeEl4ScsUqxXq54/eoGry0pJrquIw09tzGzG3putnegHVeba9arFTkl3ty/5X7bcZgmurEXXxQNjbG0VrFpDAun+PCi5tevF/z+Bxc837T8zRe3vN1NXLY1F4uGu24ko1guWq6XNZetpfaWbchUtuGHrx5wBLIxfP7qnjf9O7S54dnmGmGQlnJWnZcx8wZVhTMkZd+gwMTSklUQI5AkUFRFhV1phc0Kk8XDJ+VMIBGVyGAeeSB5RljmgFVuBiffHPmKI3cI5gCiT9wjBICdkYBf9PpGB4/z6+elZsfWaik/jKJoSc5CLBLhz6dojiIwWqGKKHEud1eV4SUoffFxJGMx3pXyJbFZ1CwfX7FctKgiRuPsmkebBevliqbx3G4P/M3nX/Dq3R3jOIiQi9aYLGBYykXZq6p5edfx53/zQ/75n/xTcs58/sULxjzRxxu0q5j6A79+fcFl00C0jPsHvnjxJX/2n76DW25w6wu+/70f8Ob2jsMw8u52y+bqEX/027/Pn/35f+Dm9VfURvxMbcGEnjx6QlUp7l+/JqTIsq2Zpon77Q5y4nK5FKFpbait5sNPnvO22/Pm/pZFW5PihFHw6OqB3X7Pw/2Ww+FAP3VM415o21Mg5YmcYNuPRL+gzhUhTlinefTkGrIoYm2WCw6HPX/9/R9x2Pe0bcOiWRBS5Is3b3lx+44Bxf5hSxgDIQa0EVDVGUPrHG1tWTaWN93E569v+eS65dOrBb/xwSV/+eNXdJPFO0MdHF574hDZ6Y6mahltg3v8LX7TP3D9rAOTuL15hW40N6+2jP0d120jsoucYQeZs6/njS3C0lMSQHQoFPMEqNnyEUUVs+AcaFzS+AQ6CcY2asWY5+mno4swcDLlPlvQx/bwMZU4yzyOVPRCEDsnhuVf1czj2L6aNTt+zjs9DgppjcwI5GPnYA43+ewDO29tZckFJXDMfTAEpFMUI6JUuBVErhYtKhm+/eFzNm3LT97ckEIkxInNas2nH33ERW14drnh4l//c+62e3704obvffWKz1++5uXNDftDR4yJrhsAsQq4PXTs0dzudvzks5+I3kLKGGuoLeSLJd1hRz/2PNzd8Z0f/h1fPuzJh8DtZ19g64YPvvVtnnz4Cf/Xv//3LBZLfv/3f5+//u53uC0cEqs11oCrHRebJY8ulqwNPNzekZURqYEY6PvAwY9UTkSejTbc3j7w5d0Wpx039zuRNxwm7l/933z7w+es24qnmxVXdctCr6jUhCbhWsPd/Y6/+vw1P/liz1fvDjRtww+/fEHfjxgt9H+rDc5q+j5gbUUImdd3twSlmLJFVQv+5f/6r/iLv/hTvve9vyakSG0cRhmRYtSZtl4y6cyb3UDvDeO7wOuHW37tsuVyUdMlSGEkh8gQDdsucNWuqIq+yI/fvuNP//qHHKYJbS1T32F8jfKG6TC8FyhSAT6P8OUZtiDFoSZlsXoMGnTxviErUYpXMOai35E1leTI6CwrOCCZ8izTcGr9vl+2vwfN5hMoOuvtzn+vOMSVtXwim/5S1zc6eIBE8SIT+3ODB8CJLJPJRlpbehb5UflrNSDzHRco6oyoc5pzmdPQTFvBb31yzX/3rSs+uNyQtcKuF9zsDvzw5SummEELC3Pf77hoNtSVYb3wPLpc8RufPOdf5T8kpsy7+y2fv3zJZy9e8B9/8CVv7+9x64Z/809+k2/VIz/eHvjNP/gN2roWLc8ozNMYJvppIMaJwxT48csb3tzv2XY3VK7i9z78gP/xn/whefWYL754xW73jlevvqDfPdAc2Y1gtGVZt9TeMe461BSptWUcBpm8NZpunPC+4ul1Rc7C0G01/NHHH7C+uKJaLXnz7g3f+e53+Z//2R9yoQ3rqwsuri5Ihz152DMeOvb3b7l/9QprM89bxccXLT98fYsLjiYphv2AqyQ7DOPELiZChBAHpnEka3j24UckU/HZ3/0d3/3LP4McsNYJdd0YYZIqTVVXbC5WNN7QPzxwt71nt89cLir64Z5nG9FTvV4vqatANwSU8qyamsfrDUYFfqc6MD6q+IsvtixtxeXja/7t916w244YTOFsJPHxTbGMGohtphiRG3LWkCV7KKqm5IzQ9JFMSQExK5yWstoqiCXgaMQJIKci3syMaXAkl50QFo6HXUqlbVyAjHkw7ijZmWIJFqeuTDrifb/Y9Y0PHjBH2vdLlp/qtuSTWhKo0mkpMwGccKGZzAOSgcyObZROxty5mcGUxVLzL37vE/7kt3+Nq8tWMBANg7UMWnO1WVBXli4mxgQ5ii+Icw5jhchmtAg0V1p8Rp8/ueKP/+Af87//a0V32JPGnoVVBBLLbuTqci3AXEoM/cAwRIYwCIfjMPGDH7+km2S5ffr4mueXl2yc5cV3/wrbrvhkueA7X/6Y/+c//CmXixYzDeQUxCe1qnl+dYnZb4XvkSJWAVrhmkpmW8rw4TCOPH98KSroOZZNMxHGnn2355/97m+xiAENLC6v0PUC7VqcvmSTBp50G7rtFX/9/R/w2U9uGQ49rXFijZEjzluMFUuBcRrY9xLA5vXc+Kq4yk2sW8/br77iYX+AaSJnaW0rIzG+aVsq63AKppxplaHW0pF52w9ElfjoesOi0jTWsdNC5R7DSD/sqCrNwkKde758d8ejZctH11f8448/ZHP5iH6YcE7GAKaYifm0aecyIOfZt1fasEWvWkSqlOBrAVHwmrTClWBh0QRlyMpg0eSsybq0eMu6TTkfGdXv7Yn8PrZxDDKcuj0pn2jpM0D7S/Voy/WNDx7n2cZPt5bebz8pzuTWOGffSUv2lNrJ98WGUEubJqf5XsxJCZWz/Mlvf8y//L1vc/noEuWMpJ5GY7Tlg7pBm9/k3d09n72+5eXtnVgjKo13/ixbmm+aqINp5dDa4nNm6RzaWIiRMY4s7jouLy9JMRQbSYBIzp4Qem63D9ztdtRG8+1vfcKH15dcbC7QruEwDvRTxyom/uDjZwwqM0wjsX8GKeE05BTFySwGEQ0OARUDddFKVVrTts2RWaq0ovZVoaNbUJn73Z6HuwOrqWexaGlWa+rVBqe9WAqYgAsZZxo2Tab2n9D1PZ/fHRjGwH7qeHSxwntb3l+ishoqT2N1OSVlwC32HS2Zb19tiAq2bcUwiai1jjNpSnG19lyqiZXTXH37CY23TP2BZVPxo6++4m7oOex7HreOJ5uKcWG53fYMQyAeXeMsaIttNuhHH5Cd48OrGr9QPIyRh9tbRE5BgdKlnJ6xj4J3lPUzE8mkKyNexceVrDVRKyFzIaLIUxILjQYt9guz3uk5Lvpz9sF5HDgFiPMBuPS1BOOUlfzKDsaBYA9ZJUQa+/wHZ/kbswbCqVxBCTvPFkhDWHbST0+pyNorRSqesBREXBVdQqUsHz9b8D/97q9x/ewa5SxZZbRvSNriUKz1zOar+OLdXoRqpwlb1MNpKjFpylmc4nOEaFBWyfh5yVGVQvxno2ZVN3jfEHPCxlBk5sS3g6AwGD68uuLTR9c8e3TNsq6oqkY8YdWCMWu+evUK5xX7aaBSCm1qdvs9jbcM3cjQDSjnyTHhlCZrI6dciGiVGLoeby1GO6pqASQqLxyVkDIP+07a02MgrxzNxTW+XWFQmJSwOUn3Kie08Szrmv/+N57x47c7/vbNjniYiHFktVix68RzdrVoqHwJmGUHKoRKqXPAa1Flq5e+mBc5VrVHEeiGAyprvAZvA0pNvHz9lmEYWNWeR7Xljz99zmEKdCFgVebpVcOTdcM4TIxxotE1Qz/R58zjiw2qXWN1QseBddPy0PdEMYY4sU21wTgrDnJRMgwpbeasQKOUIWtFLrYbWZX2ciGWzTMnaX7PKuFVOmrzwszzOJMSLN+Vf5ojkU7lOZgVDI+zVm1Jr3NOxCwWF0n9cgnIP4DgMQNG74NSJ86+lCapmCCJFFsqGo3iPzq70c+1o9aKnGTUmpRJZ6BpEZRC28zv/NpHfPLBh0Dk9oufoEzF+qNvoZaVlCMolgvHfkp4X0GG1WopkT69T0ibWaVKiUcJgPEe4xyQSdNYSotMDAPkROj2DNsHusPA0HfEGLhcNjzeLAnjwMVmQ9MuSQnGMaCUJo4jLk8srSV1E7UWtuJAxGREw8KIXN/ERF+Mt2MStzilFFZXYtqsFYdxpG089XKB9pYxZ0JMPHn8mDb11PWCZnWBqVp0TKhpKDV/SZuNwl4+Yrl7xz/9R4/5zpe3hDwyjgeax9cchkGCeNHNMKowR7WmMq648s3l6WxnkMlxIPaJKYn4kneKKYwMY+Bhu8OkxLqyPF9prlcV1wvDY+3oQ6B2lk2jWSxbtLKonNn1A3dd5DBmrtctoXK0dmS37xjQUFz2UKCtwWSLTgEVNdZ7iJGQKHA9R2FjKNyM49I9ZcqUGRbxyxXB7nM7iJ/e2OfB43RyzuX2/BvqvcdxVrJQMBNJaWbZy1/0+sYHj3OMYv73z3u/x4nEUg9qJQY7VhusiozqtKHF10XLYJyZTZxl6jWpzHLd8Dvf+ojWwrsvfsTd63e0jz+g7wZ8u8TXHpU1NmXGMk6+Wq+4vLwslhCn/vxJ46FwTGJAx4Hc9wQt9XDOgTiNSFu5nL4hoSewKaODlBvNakFT11RWjKGNc5KpxMy+79Aq8smza/bbA/1gSzCwWJVk042BPmfGIJOjMQr4p7WhsfYof7BoWlQSo+iqiAYZJe5nMUYuN2vSLrFcX2DqBaZqi1SeIUwJa2tUb8jjHozHNg2PNxUfXdTc7CqWrafWmYW3TCETJjm9jwZKSkBolRXOSHmjgco6KmfwNtNah9IecmbZahatEe9apSFGvFE8v6pZVIZD1zGFQGMt3RhInSGbkVWlGabM7bbnxb1koAuT0F6zsJnrRnG/7bCqpvKGcRLsIs/lrjElXJxo5vk8Iz4D4o9r9FhOS+s/KdFQtbqM+J8FnrnVOrNXf9biV197frnOQ89Ppxjzl/9V55P/wvWNDx6ngKGOgSSljNbvB5TjVXrqFKxbzQzTcq9TBqXKDQI4dnOkzYvSZJP4+Oklzy/XdHc3dK/f0NRXtBeP8c0CZ7yg6koR48ih27Ptdnhn2R86lquWyldluAmxZygLxmpFSPKHaesxvpKFmCNhGlG7DuMq8jSK2ZMW5XVvDPV6Q0IxxUg00LTLYoIccc6y1hWjV4yjwZOpK0M3DEyTYCbjcGCMI+M4sR8HDuOIVpa2XdC0C8iJpnG0raeuKtq6oa4cBs1hu2W9uaCqWhbtmnaxIMeO5eZS/FpyLmWgRWcPyYNfYGISEV9b0XrL736w4ct3e6rW4TSsq4q3QZTe0RmTRZE+RCmhwMAkPqsZRQBRhwsJXYG383h+CW46sWxqyMK/GfoJpwKHfpSyISYUljf3A9/7/EbsJ9Yr6srTx8DVwtMoy5vQU1UJT8BnMCjayjFNji4juiJqPrBmXKOwkudVdbznMipBBgrXxirERU6JUYPRGqsEVLdaDC0T4tSnVBbvYlRxMZwDxan7cpyvmbfBfGC9l3HMlIVIt9/GQAAAIABJREFU5iT6/Yte/2CCx4wcS/qfSFmTS5p9HqVPyJDI3AujE5it+pIq/faCOjNnBmpWH0QbzbeePWblLMPbO1Q21JePqdYbfNNg60pGscLAbv/A/f0dIQacddRVw2azwTt/XEzkmSp/ErA15cRK0wBafFniMGLiRBwOlOOmSCdKRgAwBXnP+75Hl9dTSpHiiCJiiSKGEwbiOJJDIIwjU9cx9COHw8B+GJmyYr26ZLVsTzL9VlPXlnbh8c5jlcU6yzRO+MqhnePdvuODjz+C/QMXywW6qqT8i0HEkLNYSMSYsErSeJNjsWPMPNss+PTxmhe7HpMn6mVLGyLjXJZm6PpISIFxDCRjidEQjOiIhkl0O6zJjMHgrWyU/TCx62SYzqqeZW1wOvH67R1jGDBa83S9oHUWX2kuGoPKLfs+8/r+gHcTIRoebRxLVXG3D3idSGliGEaM01TWi7aJ1sVmYh5vLW1ZpYq4TzribLoIAhktGYnOQl6sjMLPWETOGKNx1ohnSy5mU5xKDAWlrOEI0AqGcfI8/nqxc85b4ozExtHUkvcrob/n9Y0PHj9reGfuYqTioWq0Pva1Z7OkGaLWGrSR6UsdZb5FskvZwDkLpyNrhTKCezhn+fDyApcVXdehXYNdbrB1jS6uakopxnHHOO1p6or1csXQ9WyWK9zsEKdO2pJz1yeTjyIt5Fn8VlpwIk0HBi2+uOX3XFWBkhNZp4wBVssVKMX9/T3ee4xWpCiDZcMwsNt33N1vGULkoTswhUDOCuUsl8sV3te07YKcJ7RWVJUrsoZnDndKY62lHwaq5RLlPToZKpPIw57Vs0/RlZdhQoAQUGkSa0XjSarCmMRw/4K425Kmieum4tNNQzdODDnQGEXjDV7P1hMaZxqm4AhjJIRUgq5imoLMwqRIpyP9ZPDGAomcIm+sorYenTMp9zibeLRyqCkxpImblFgvK54uNqxdReMdIVvebUde322pfEVjK0YiLgRqbbBWkYg0WrMrg5VHm8dUMqQs5d18bsnGTxI8VBFVKmMnJpeBPqWoZ4pAKWGsEs5HLkF3QOZc4Az4lA1wgk6Oh+d51vE+6pGPB+X7mfov27L9xgePE9HlrMWa83FsXiJvOrZqmauW8jPJOGYj4FJLq1NbFqVEUcxoyJqMom1rnl5uUCkyDQPZrtCuKq08JQN2zhFSxluRDGirmoWvaar62PrTSpUTp/TZT+8Kio6DVuLempVGFQOrhIC5MSaUtTjF8TmdESe3KQT6YcR5hwL6YYDCNdmOE7e7jqHwESrfsFw4jBHNkaxkTsY7B1mYndoqFosa7yrxaC1zLNpomrbFeE/MhkdXG4Y3L3j++Al+dYFxFcoYoV2HUGY1BBg29Yp4iOQ+Me0OWK1Yes310vOH/pr//OUtTIFV6xmHgWmSwwBrSNkz+kjfjYQyyWqdxShFTmKylTIEBPQeC2bSjWKYXVn5zBrn+O1PnlJZMcjqhgMLXxXexSB6IWSeXizxVtNYRQyJpYnUxlBZAZfDNKF1VbpfGescDhHWSWSsykVX5ZQFzAOaMM9bgSuSuZWGRpWSljJ/pRNGyXDFhCKimFQZfit06ROiMc/azhO3cx0+YyMceR/lrJRLqdmE7j2Q9Re5vvHBY77Og0hKUTCK90BJ+dC0KqpgJd0TlS2LUWCYpGZWZeBII201pVDKkPKEUiK6vGoX5NQRxyCSgbqIvsSIIqKdTOammLnf7qmM4/r6Gnn6VBzLpfZVRp2WlKL42E4iN6i9WC6WbEnc3iecd2gvJtLpMGGK85w2likGxklKCasVKSZ8tWAaBkzyQjV3jsPhQNcdCDFjrKOqPNoY0fRQitVSLBcUopZlal98WETdvK4apjBSeU/OCrfcoHa3rLxneflY7A1RqCiCxco4rHYQ+9KSBEymvlhjzCNSf49WIx9dLrm57/jjD6940ScmX7E/QD8ohiCtzpCgtoZl7emGke2+YxgGoXNbg8mF5BelNb6sPdZIUK6qiqfrio8uaxqT2e731BdLnlyugI1YPUxBRKFS5NAPLGvHR1drNIkhZx61itppVEqEKfC2v6NZP5LReWVIWtTco7PEGNBGRv1nqwMR5zlpzFilcIC2Cp80jTZUJKzOpTOTZZhTQTbSyp1yMcTmFJSgKIIVfgl5XltnZJCzbP08YTlyP9Rsl8mvbuZxnBKcEecSLHLK70nhpSSWj3O0RamjlJxBJmztUUdyjrpngafUsJQAtKorGq3Jk3jD2qIhocgQJ1SSbMd5z91hz6E78OTxc+q6Zr/fY606UzoT+Ty0KV/LmDtwlLlTShEnqV3ruuaw3zGrqWujcYsF1lpiiHTbLSkl6raR959gDAOzkrsyTqwYBlmMi6YWcHbOZFSmakUPtm1bmZotqu3aWoaxEywJaNuWEJ2oeLmGi/WS4e2XXDx7jvU1zngUojA/e95MYcIrhQ5FsSxlolH462vG24gd7nl+sSBMkWcbw2U/8GbS7KolXd9z6BNdPxFnuoJWtFXFurVs9z27TmQY+ylgCoA4OY23UHvH86sVjVPoPKBTYrPcsLreYI0ip8gwToxDAKMYxomuGzBOpCunoWPdNNQuyfSyjlir5HdzKF4/klEIlcviomM0AUsmpFAG3QTjsFoVnlHGkIs0RMIbaMi0SnhIxxY0cqgFBVnJ5K0p2czMA5kz2GPA4LSef+YeyqfBuNP3KOvul+rUfrODB5y/6aL2naIkaumnsw4yhU2XCt4hXhlWp9Pg3KyjcN7ekqc/ts4XlafS6mhNeUzvkqD1OQRS16P2PW/fvgUFTdswTmO5IeqYJZ1rPZyu0xBeiEH8XovIcAiTmFRZkf5DJ5SR0y2GQL1syTGRJpESHGMihXjklUzjyBgiBkXjxQlujKKCVnsBN13xX3G6+Jwa8WUd+6GotWuMEnq8dw5lHO7qCertC2pvqJcrlLWAkOJEeV1mJVxbk6dBSHcZ6EcxF197dN1gqgOGnmePl3x188CjTUU9wkP09KOlO4yMk1DYD+OIto5uGKmWC+Ky5qGbiBgeHh7o+u74iWqtMClyd7elWXmeP2rR1nL7sOXd7R2Nd9ROcB0h6GXCNFFVNZbERdvgXWaYepxpWS1azHSgrSquViu62It/MMIbogTjjJhNSyWsSrYppk1GZdGD0aocYAqtMj4rqjl4GPnsZpOnpDWDUiStsEmVsoYzKPRYk5clm99fWsd987WgUvbIaT/Js/4Sicc3PHicRcyZTKNy4duVTEF8PjhK5eW5RlRFMMVklEny/7m1dlbrqVLCYIqLm4ZlU+GNgSnKRqUEgZjJBOh7GCcO2zsul2uCHUDBkALWKrT3BCUNPCl6TQl4wnyVG2rIiJyAcY44ToQwYZ0t5YCnqVpijAxjRwwTOouSWZ4C4dBjjBU1c62l3o4JQ0aFUUDkovwtavP6qE/iXFUYq1GsTlIqpk3iOePrFqs1YehJk4b1FV5ltjevuHr+XJS8VCKH8QwITqiUiv+iJpfXyAr8YkM2EdOsUW5H6A+01vLscsOLu1s2bcNF0/Bunwhe7vk0Zu62GbRhsoblUiwuQ1xwGALdBnJacbFeUzlNChNWB1HZt57FwmItHHY7wgRhEnZnzAljZRMt6oZWQeVFkGnsB5xzjCgWJjNlIyViiqzbBa/3A9ZUeGMZUmI/CqagddlIOUmBYXRpHwuHyFiDMwZDwgSNVRlvNF5BhZQhViuUkWlbtCYooZupgmPIATnjGGVd5Tn7/hl75wzoEAB1lkzMiGqIdIXSz/zl/7brmx08ynWOd4B8JinPoBDMpB1ZxHKJXD4okpQvs7fIrFMaT7oIM1g9jz2v2wajMmEayUkMleIUSDmicyB0A1kpvNM8f/ac3esbMBZDpnIObx1KFftArY65B0qRtRHMppRW2mjGUdilxjkwnvWF5/7dO6wT6rxDCc3dQegHpkkYqjkmDMiQlfNkYBwH2roWhfIy4GaNZRwkKyLDtO9K0LJkU4BOwFqDMhbnPM5Y0tAx+oqrtub+B3/Fcr2i2VzimgVKSQtBW2mdhynirCWO4iEbc0Zbh14/x9DBdAtti14uUPstOWY2y5ZgNF++vOEiZi6WLdEaUgj0BMyyoZ8msBVew2ZZgzIiR3jlpOXpPVZbukOHypamceIsaDV141lXXuwdpkQi0Y+BYQr044S2ispr1qsKkyKdymyHzHK5xtkHMZJSmilF0BHnFbtxRGUhys2yhHNb1WgjQsXl0Du2aeVskjattTiklLUKXJID0GqNsmLrkfVpNksW5vt8jOO8lDplO/P3f3b5ko8t4dJT+KXKlfn6xgeP90lgguLPH+yMg5xa2dJZsUaXkkBKFqsRzENHjJFBJGUN01TUwrDkFEWPUxlWlUxzqmmSzGOcCOMIOaGtImEIgGtaQj9isywYbb2ksynJHER+/w5JwDOyokr2NHNXMB5rNDlMQk8nEGPAe9H2VCkThpF4GESx3EqXxsiwuJhuG4Otyij/2eLSgLJCg5+mQEwRU8ym5wgcY8R6sbnIOYupVLWmalru/+6HrC6uuPrgU2zToJ3HZJmJmSWytLfkBCgxYpIS0ZCmiZA0KoC1UmZpX5GGgTT1rLxmuVhx83DgibM8vtqQ4sTDQ4c1AXtIKK3x3tH6hkPfF7c7X05zLTqrxmGUL9iWQSnH0EMqxuJWZ8aQGeNEP01o63Dasm4ttcukoFA2066fYIYdKUw4bTBJUSmZvt7UniFnbjux1szMnTxTMtsZkysWlQa0zhI4ZsyjbHejNRaO5tdGqcJLgqiR2RfmPX+mV6bOso3/UtKQT8FkxglnAaO5WJcD9lc88zhd5/XbKVM4n6ClYBtZiYamMRodhefhjSaUejKK4rHoIOhM1AalLVplWmfQKUEZN5+CmAmhxbHdzt4iKRJf/gTX7xn9Am0F90AplJfWbk5I6zLLdKMqIj/KqLKwdQloInWYc6JqF1y6ipvXL9GqhSmQQ0CFRO0qUALOSbWWJMDliD5Ky82Tn0IsCjEw9QPG6KNGiFaaUHxflFKiyl5GvrW1JGswzjG8fcmqbllfPcM3S5K1ZBTZmKNobI6ptFAn9HxI5lwIYoo0DuRxQvc7cjdinBecZpIhtU1teXETeH1zz7KtWTYVq7XCVJG6dnSd6IzEELBa7ntlHVVVkWNE58hq06IUTKPoj0R96qIpo8kp8bDdMoSMtQ5jxHXOOiMAqA2EydKkER23DF1P2y6wOgMRrySw+qZC3XfcbHv53IyRzKtgTiklVNKFsyPYkZ7XrlLlHsmBJzR0XVxqZ2RDHn0sdvOcXZzwOV1+X5mz3i2laZsFm5PhwkRMgSNqUjwbZh9cVDlof8HrH1TwmH0oUs5HW2A903BLRJ7bY1KLnkb0ZVBOPizxtZV6mhwFNzeWZB06JbwVn5hsFMo4chYCljIKU9fga5xSjPe36Pu3NNue3F4yWrGB9M4Vog/HqJ9ykq7FnFoquXm5nEIpTVhboa0hJBESXq4WPNzdsW4XWGPktZOAqkYhrRatCXmSVrJRxFBOGS2ksrkLk1IkxsCUhJYcpklOnlK0a2cwzkiGUjc0148ZXn7OuqnYPP0IUzeSmsdcWt3CTyBJmzbHQByGQkWHXCaCVUzkscfmzDSMaOMgZqw2YkmpYLmocEbz6u7Aon5AXa2YwsiYMs446soTUkYZcNZBzgxjT8rSJVLaUFWeEAJTH0hBrCyq2uG9dLmGYZRxe4cMThIxWrpPKWcGKrxNtPleSjktDOJFrXFOuBH348DNGHm0WKG04+Zhdwzg2ESMnAY0MfOUxBmR6xycl4CR56/1CVSfbRHOuynz+j7Bp6duJGWdvQd+ZDj5tOTjYTsHIV2mx43+/0nwmK+ZK6GLYM5Rx7QwN+VeqJJSZowR0WGlZ3bnSZt6pkRTAoxGH9uWOAPWCUErTDhr0K4hKEMa+8KaDNRaEaeRzjqsa/BNzfb2hqVpcVqfSq+ciTGX2taAlo5F1ppspe5NU4AERjvWq0s0hu3drXjjeg/KYFOEMDF2B0gRnRXeWALSCtYZQpGhm20mKZ+J9w6tzHF4z1Ye7aywWI0ne0+zXNK//Ak1merqY/CNTEMUBXHxjpbXUihUKoEqSKYWpyiZW4iEw5582IOe0CERQsQZyf5U8bSpnObTp5fcbXt+9OItSmWuL1cwjtx3e4Z+whztjaBpGoaho6oSda0IOaFUse5UljFksoKpD4X9qkQvI8rnb7S0ZqvKErVhRNOuLjG7V+QpElWiaSr6fuCy9lwvKl7dT1S2wQXD3WFPXXmcs2f+r+loqaG1RskQ1fsYRP6Z/3l0eJv/eQLJzq4zbsd7GOD7cMjZw89pDjNQWg5TTgHt57V4/1uub3zwmCUIlRI9x+OAEeU0V2L+q3VJ1eEIDM4pni4tMWs1NhgZqisTtiDZi1GJpA05CVYSjUY5R13XZCz1wmPrBVkZOdlDQsWEbdfUjSY6i0qRynvuHx44PNxzWTnathUGK4oQE9lwNJ+SutPJJtaaHIN0WrR4xGhgs75i2SzZb7fs93uZorVG3psRtuhMZCr9nSMqn8iEotmfQTxPtMFaKVFSzkIvd55gLDmNmPsdh1dfClX7yYd46wnDgDGGKfZYYzFG/r6sFWkK5DCRxgErvXKsK6xaxNpSGcPUH4RarySDMoua1HUM2y3OWD54vCZm+Mvvv+BvfvSOD3rFx0/XPH72hLGpuf/8Jf27LSFExmFPSomuS3gfMZUXK4VpYorg64V47+rANI1UVVXa2AUADYlmvUFXFU4lPCPm8IaoJqLWWOUYhgGlFC4mKm242jS8PAQerWoeDiNTilijGZmTBunuWSDMjnCq/KxcGY7dDZXVyct4XrPleVAzf/Rr2cqcUR/LmVOJ+FP7pvzwhLups5+d/1G/wpiHMDUlgMzvf+5tq/Jhy02hBJf5YfpIvpFIWwAsI/oaRkukT4WIk0sdGTK87TpGBaby+Nqifc3q+hK7WBHyRBx70jSRs0L7SpTDmhY/Id2MaSJlOe2kPVjqbA2RIGVpSlgj6aMyDlJkHq7KIYiOhbw9SIrN2rJsxdRo6A5SRikEV4kRZRJTzGSlQWdsVpCEN6BKrSvpqyJbjza5vF+F7jpS36FyRKPwVYWpK5SyjN2AsZkYDKiJjGIyImWgjKTmRkstP+wP1KuWME2kaUQbhbKGFITgZlHYqgEUU39AFRBv7Ebq1ZKPHi1Yth/z3R+947Mv3nLz9o7nz1ZcPbvk2SePML/+EYNtePjRFxze3RJjJmQIITAOgd0+MkXARJxzVN4xJfBFGlI3a3KG1hsulhUmT9gwQOiI5RRHi5+x0QbvPSnAOIx8dbdnmxzWQ11V9J245CkSZLGANBrZjFrUCXS5hz8t/yevldSsczpPZGbmqKDyiYMhxW1pgRfPlcJ6P7uk/NIz50kdIdbTa5Ymw3vky19ib37jg8d8zTJvX/um/CtlspYAkPMpFTsCqiWVNEbJkFJAtDOnKB0PNCoLB2IEPnt3x24MbKolVLeYyuHaJagEhz3psCNGxJEdoLIo7xi6A6HviFOkHya6KRJSFk7EXOOWG6yLl+hRr0Qp6dYogDKHkwRTsN6QwohRitZW1M1CiGoxEMJEripCGNGDKIOncWIwAZ0zNkTQipiECBamQOp3x89UhvMUtTboIonomiXVYoU2mjD2gMU7JcJJMaGTIUcpPYx2ZGdR3uBVA0YTxkCljXjeJnGnz9qRlWaIIyZCDlk6JSGBhjCMaGu4Xi34X/5gwZ/XFf/2P37G377c8tHynseXb3jyaMXF0yWP1i1686H8LcagrOd2O/D5T+4YD4GcM0MQb9eYDcMYQClSVFiVWLT8v9y9ya9l25be9ZtzrmqXp47y3oh771O+fMp8iZUvU3LRAEumAxJyx7hDAxskd8CiicVf4G62kCwkBBIIEA2ggdxBsgWWSNlOZ+HMV9wybhQnTrXrVc2Sxpxrnx3xXuLMe0XmxSu0dYrY+5yz15pzrDHG943vgzwGRUnAOREFjPeNbYFSBSFYssxxVEo665BqFK9JIuYZY6PBubVR7S4uugjPi4CQw3DcUJSk9XrQrYgZ2v3g2vtlxC8EXtNa8qkJ78N7g2/hAKU8KIEOv/dtdDyG4/8XweP9+Liv54gMvMi12p99gH3deThfEEejBwf0sOdaIAMyJGdymfHF1ZLXdzUn58dk4wVOqtjB1x1us8Fu1nQu4ILBegOUuDT9aryPN5JEJDIhoDxgbXL0SjcZmfoeKaCIJDgiAJW4E/FNRg3tKMMY6dEqKxEyi80+Zwne4I2hVB227XFBoozEao3VHhcsmYroSi4lGrkv/zwReXHe441hVI0pRxPK8RTnoidKUZQI4fAmoireuWhclGeRVp2pmPGEEHtDKsN2XaR09z2ZB58VONfjvaBrDTkBYzUqy+n7hlxJimoWsygp+P6HJ/zDf+r5+rJjOTI82Bnmi5bzyzXzSUVZFJSlZFTljMYTOispspLZpIxNYIYgLdPGCiAdXlu2m55xPqI8qghOI5G4AN4O7OT4GiElynkezirKoqMPsWGrjU1ZYeR4xKFFtycfxtIiZmR7tTtSOcl+lzMMTCKGDPugxPgFrRKx/+rdtulQ1vyigLDveSSex6G26bc9vlXwEEIcA/8V8EPiu/qPgJ8C/yPwEfAV8DdDCEsRQ+pvAf8u0AB/K4TwO//K37E39Hu/kzw0TgMBlyK+xCNAqD3ColQUXbFEanAMIBF/lzJEBbFAGqiLepB32y3/4s0bvvfw3yA/eoTsN/jgCH1D327pdzt6D53wrI1mNjklyyuQnt1mRY5gNJ2wM4ZN05ONKwQWpE8QaurhCPXOm4kCLUSoTSQI0YOXAVxMfGSWEd/x/aSu9wFnHQQBmYos0gQ956Mx2pjYTLax1Aldu6/pvQ9Yb3A+Osvn1ZiqqsiQFKMyzQwJgvfkWZ58ZKMmJypD5vk9Qc85TLMlZGVEVYzD9AGRjKh9CAgv6Y1PKmFRIdx6h9YtuZ/GJkEwKAnnRwU/frOkaWtq0zNvRtxtC47HFbOjOVWRMy4804kgLyKzNE7BRtGlPBMEmeaagF73GCnAgncCZ2J5EIWY0nS2BCf8fWovYD4acTzVXO0sve3i30/skxnvMN6S4bk3+g1J8EfG9ZbQk3uMJMAAl/o0+ZrKUxEidwX8HpULDDow+yuf2NYRrxng3PezjOEGFN5rsr7/+KbHt808fgv4hyGEvyGEKIAx8F8A/0cI4e8LIf4e8PeA/xz4d4BfSo+/CPyX6eMfe4if+yQew7xIPDnynRNw+LkcCDxycJQbusy8o6g+5HxDJtKFwD/9/AU/+vAZPzifIkoJ3mH7Hl3v6Jodncq57jStVGTGsXnzhpCPME1LMZ4gk4mRNgatJbLIovpVljGQsoKI8n9CJGd05+PHuLZSaZyCYVbEGjmabSCkj1wVFXU3cpWjuxaV5WnqWIHQOOcoqgxnNEplGNPTdV20ofQeoyMtPctz5idjijxmNaqsUEXSak3Tq8PhpYiK7zIjKwpCFhduEBLmxwgH/a4G61B5GTemCwm7lngUu9YQTIsIUb/TZNF+IfJPDNjArz1/wD/+8TVL7WjXNeveMK9yamM5QnAymxJUhteeaSYZF9l+fCHPM4pMUFVEzoPzlFlF6wNCBTI5oFEu2i0JlWwOQnS5G+5OKASeJ2dzTuaCu13UOtUebtYrrNORY6OiAbg2Bog9k0xG8tc+MxhgUzHAqEPj7n79vbP+xftL/z6H8d7vDZzeDQLiALa9f3U4QIV+MT7zpz++cfAQQhwB/ybwtwBCCBrQQoi/DvzV9LT/BvhHxODx14H/NsR3+X8LIY6FEI9DCJd/3O8YUAPej5LphL2r83jPpkt/3/7jIGwjZew/7KXdSNkc9+daSoUSGS9vN/yfn37Kk+MfcjyZRT5D3+Halr6t6YLkut5xfPGUcVWiA1yvVmzrmtl0xmKxwJqe/OSEMjgyOaYocjKV7QPGcAxQ89DYEkMpk1AmZFTgRkmCiYS1ICJJSwhJcAZru9i3ESK6mTkTLSFlRKmMjcrkXco6hgDStYZA4PHjJ0yPTvDJrEgVJVkKHiEEVJHjJZCYkVHuRkJZIJI/jUMgxRzXdcixw20NxvUIldHtdoi0Ub21BAe67pHOklcKlQdCXSOTnJ/tWj6YZ5zPx3x5o9kaQ+c9vbVYIQlVSTZyKBsITqIcZDbqaohUhg1SkVIInA9IH5hVFcGAFCZxYGLT09sQMz8R7hEQAgSJdoHlekdezdjsGjoD00nF8XhM25s4EJjF/pAI0Tw9k8kvWQxeKqk355OZeursD6Hj3rQsPQ7Yye/iJUN/Y1j799nFsBd+fiMN5YrHufgYIGZjzM8//094fJvM42PgBvivhRB/AfjnwH8GPDwICG+Bh+nzp8DLg9e/St97J3gIIf4O8HcAjqbjd1JzKe+naIdjXzOmjbQ/0Yk8JkTE9ZVyZD7ywuLLoymzxeNFwAufkIqo6qSd4J99/oK/+PFT/sL0CR6H1xqMJvcBnXgMbbuja2pKWVBmkpP5DKUEeI/WhsV2i+sbqkyS5xEqFUIhRbFPJweqfcxcRXJC93GOTuWRSegDwkqEjISvoer13keSVlqUzhqc6QguGj1ZB94FrNM0umFXb9FNz2a3Zde2SJHx8OIhJ2cPGJUVWV5SlBOyvEBk6U4XEqSsiNwMY1MwjjyYmEJ7srxAB4ezDt9HCrd1FqM1hJx625DnKgESij4oTN8wzQp0bWJzMY20e6cJSGaTDLHMkD42CHe9RuYZVWvI8ziopmRBkXu87ymUYJzl5HmG9gHRReEdlVAIIX1slnuJMTrNp7iYEQWiBEMRofB4TRy5kjRao0KPCYG3qyXH4QiE5Hg2Zb3dsGtrJIFCxWxj0CiVMhCQ7apjAAAgAElEQVSkBSf2/KJBPzeC6Q45OFcJGHxohE9N1oMy1wODfocPjug+l9Ce4Pd9O5+GRFW4D05pV8Q9k8rcIXh+0+PbBI8M+BHwd0MIvy2E+C1iibI/QghBDLf4P+ERQvgHwD8AePLgNHjvExHsIMMY8O90YhmUwpLaUmSVJjEeEbU14tCS3/dC7nH1+ybWPkNRBUIa7lY1f/DiFd+7OOFITvA2UrutMTSdQXmP1Zar61tOTs/ICQQl6PuOPMuYTqY4b1ltd8yrknJUMkmSeqmG2ksh7lGiAWojNuwQMaAgQGYq9XZiL8haGwV3vIzohyCqv/eG4OIi0bqlq3uarkNbzW5Xs1ytqJuaLMs5Pz9ldnSEyjL6rqccRe0QiD0Zn3oc1sVZHe96gjWoogQhccZE1MmYSHEnQ6oC8th81JsVwQWa1tDaQIZHyAzde3RrwFr0LkKLxkRRJEEgD4Iyj9TvvMgQ5DhrCM6wbZo4vJcXlIUG4rTs0XRMEFkkq/WSUZHFO64IlFkMwDiL8lE1XiVdjjjI5pMsQhofGPpSaSReO8Nmu6AoJpR5jnDgjKVuaxa7NVJ4qkwhUVGw6GAoTogQ0ZjAkK9FJbwg970K8e4muN/wP0fiEvsb6n15Et7LXDlMRe7RnOF16eH+HKHaV8CrEMJvp6//Z2LwuBrKESHEY+A6/f9r4MOD13+QvvfHHoeNnvfrtP0sC0S+wcHI+eH/qaDIPLhMoGwMQkOQGPofQ+kSf65Mjm4C28OXV0vquuNoPkflxd5/xdieEomTGSovqMpIvLrebWj6OHdydXPNB+cXzOfHjKczZJaTmBYQQGUHjuvpLhPpzewXxVAjI2Mq66VEZgrXd0C8yxlrkQktIKXG1miM1rR1S9003C3XdNqw2m6p2x2TasTZ2QUXDx4wGU8QQqC1jsJKSmFNj/A91sZGorcmzsUMGysrkEWJLHKkkHhrsW1HnueYrkU4R9dreuPomo62NwSRIbLYd9m2lm3do3WHMT3egdYOqz0yD8wzwXQ0YdlG0SUSQTA4sLpnVdcpY/PY46MoRuwDs+mYUGQo65KEo0Qq8MaSCZ/g5sg0tc4hGVih0bEtiNgfGDROYg81cFqNudlu6Jod2liOR4rF5o5t12KsYZSTtDtkJCYnDY+oAJ9ud0Mw8T4OXjIojr27vJNF8kEWPWTbP78PhiByyCUJ+4Dxix82eJwgDU++H5z+5Mc3Dh4hhLdCiJdCiF8OIfwU+GvAH6XHfwj8/fTxf00v+d+A/1QI8T8QG6Xr/7d+x3A458ne6/EIGWdFh5OqpEgBRO0DiEoDPyFIVBaJYFLEuYZBmDbeAcT91SJdKBVFchCaTdehjSZIRT45YnTSYn2glYrgPX0u0d7FEkDmQMblzRtOjo+jnmkIlNUIn5idIaQ518QwHS42aRELOJCjjGUUIkKrzvmEfMRMBWQspbTF2R6vDcE6rDG0u5q+banblpvViuW2prWW1XbDZFRx/uAx56fnTCdHlEUJPtos666na2rIBFY3mK5jsVjx+vI1X718y+16Q1mNeP78GZ988hEPnzwiL1NQdR7bBpzW4D2m09El3juariUAje7ZtS2LzY7bVcNiu6HpWpbrGu8VT07PKHJQriG4jq2Js0cmuChRIHNEgp0X9SZa7+QFo2KEyyVFXpEphQM6H7EJ50Mcg8ehvEM6C84ClixNWkPsFcULMJQGAY/EB8tIwrOzk5htyRUbvWPVtYQAKvjkaRPIVJweVml4OvoDxVuGEJFMJ0Nae9zbM+wDgyCu7WEtMtzc7hv7cWEPiYbYf+Odvt/93TDJHPJzN+F99vINj2+Ltvxd4L9LSMsXwN8mQtz/kxDiPwZeAH8zPfd/J8K0nxGh2r/9r/rhCbXcS87vm6HcN5YGBS4lJcgIU0YCViJkKYl00UFOpe63SqWL/LluNvdCs8k60Hi7N0YqZnPGVYmaHyM2a+Zdy6rueb3bcdm3XG93NK1lu13z6PyCvBKUeQkiDlbJRKO/b3Yd3FVSPSwCyVJC4oXfT7pGDkrcoD5xITwHWVm6q8QmaIsxlrpuuNusuV6t2dQN266lKAtOzy44f/iY0WiCUgUiqCgHkIHpLfV2S/CWrl7z5uuX/Phnn7HcbSmmx1Tj6Ft7e3uF1g23t1c8f/6c6XSKUioKHvlA33YY3cdx+RDQ3kZ3uDzjenXH9WLB5XrNq+sFr2+WtE2PRLDc9TyYVWQlWA/aWBwZrTZMRIlSGUVRorzBasNqt0PJjDIvqfKCRhsmCa6VIgpbW2fxHoJx5ARyofA2IIIlZIn3kMUxh0i8ivCxFHHcP4pij+h7j8pLLozltm5jyZj6KHEEQpKpFDhU4pkQL+rgSL8Xw/apQTvM1A4/a7/Cw36w7rAqCftuF+xtLdPveH/zBOLeiWtt+Hi4u77d8a2CRwjhd4Hf/AX/9dd+wXMD8J/8KX8B98Nd0T9WpB6GFAeZh3oXvXhninEIMEMX+53/P2hKHRxKKlyyiMTJVCAaDA41mSLzkklRMK53SLkhG41ZqYxiMsf6qKo1GY8i1+Lw7RDRHAbi0AE6JIVILnEuvm+1P2+Jxh2nYUUI9wbYIs7LCMBbR9d3OBcblnVbs6prrlZb3q7WbHY7ymrEo7MLTs4uGB8dI2RG03Rk0jGpxmRVSfCerjd0XYvRlq3zHD1+wrFQjKZTyGKJJZViVFWMqxH1psb2lvGownuDNw5vLbu6ptOa7a6OxKoAy/WKy/Wan7y65Iura+pdj7EG5yLb86u7BZ0v+f6Tx6mR2dNZQwiS3noKGYl1QuVUkxLbaRa7Gqlu440jk4hckskowegRBBeiJKKL1hc+E7Gv5Tw6xGyEpItrbbwePiRBfWIzfjwec9NtuV6uGVcVU+PIlMCYyEnJFeRZoMhCDB5SpM019DoSI5SooRKS3sswQfsOcsj9hh8yhndXaNh/fJ+rcZhdBA7Kl+FnH/ZA+FZVy3efYXpfq8WvxcHGeycoCLHP4A6DQ0Q4o5akfCd4DL1WEQda0gUeZmiiKHJUZRAe6DW+a6M6VpaRFSVedygJ62ZNW4yZjee0SByeVmtarymkxOM4GRd7abpwgO0Pk8HCAy7BsCGOSos09m6Njs3IQDJWivwE7ywyE9je03Ydzli6pqFrW9qm4W614mq94m67RSjFh0+e8OjxE+bHx/TOsdvVqACz8QQRHP1uG8+jc+Qyh3zM+OgCV3b01rLsNYXPMAi6ZsPp1IDnftCOgO57+rbDaUNdb6m1oTMO6x3ruuanr1/ze599wdVqy7brwYZIqSdgPTycFfzSsyc4bdHW8+ThI27WG7a7jk5rHIFplmOdj1yassLTc7PZIIUkzxVVmTHKMqz3SC9RWYbTJq0Jj3YGGXw0JndxbTCYfguBkAqrNZ5Y3hpraVqDNQbrPArPuFARdvaOMhMUGRS5JM9ShjtMr4ZYbroUEqKnTNzgB5jhPrUQiPuMQwzZKXtUcXj6ED8O+v4He2YoSQ6/ef/8d/or3yIB+U4Hj0P+BqSULWUe72Yg94Nzg6o6sKcmK+HJhEjM0sg0VTJaOUbJmjiKP8T8obwQmSLI2GCjt8jeEQpDKMrYMMxyghC8XS0YnZd4AkU1xlq9V+oKweP6iFAIIXCeKIf43h1DJAEX6+MsihACZ03UvVRZnGFwIfVrwFmLtT2kksr7gO56tI7IyvXtgsvlkrfLJW1v+Ph7n3B0dhZJXQp6r2lsFDzu8ORIgpBc3dwgpcQBt3eLOE8znvD5q5eEXPL47IKb5YpOd0yyjBGB85M588mY87NTxuMxk+kUE6DTluVmS+0dN9sNn3/9hs9fX1P3DpEVjCtF27SY4MkLyekk42wmUVg2pmPbaDba8qMffMzNYs3P3txiQ2DV7ghekLceoRzjPMchebNaRdc1AbnKUVJRyeiyl0uFLEpEsHhtCULGUsa5CI8HYvD2Hu+i2pokSgn2XrDrNWVeoHpP01vGhaSUEi0FZSYos0CezMVyGd3tIreDfQk6HF4M6zogQnS3T4DaAJjsqxCf/sX7zT0yIw76GpGd+v7eSSU/A8ISnxS4z3b/vBmmf2ZHPLlD5iBTEJD35YfgoBS5zy4OsxOp1MHr7t2/rLi3QxAiNWSliOK1KqIr3nmC6RGmROQlcjTGB0O9UHz49Dk6K2lFYDousD7DOc9ut2O9XHMxqRjPprH3kTr5IYny3Ceglq6rEUCWl8kN776hKtPdJ7JHU+08SCT2Gm8NIVg6o7nb7LjeNVzVNVvteHDxkEdPP4yp/nTGpu+4XW2oO42SGbQtVZ6z27Us12uKvOBqcYdHoOsWCbxd3fHg8SN+9uoVzWaTRIVgWuZcrhdUUlImEaXZ8REyU+g2EsS089xudvRBkFcVzWaLyjImk4rJOCOXgnW94ZMHEz5+fMrNcs2D83O4WxFUyc3ylo8/fMxkNuaz13dR9T3AVzfL6L+TRu6d93z+9hqR54wmE8qyiEbmCW5GRFU4QZQxEC72ZzCROFVkMvYaJHv9EhkkjXa8WixRqsSLHB8ENkChYKwChYQiE+QqUGTRTiHySmI2hhv0wdJaPujZDVd/ON5paob47HfAgv16F8ML9s8/vNHuy/H9894NFn/usy1/1odIJ20IIACHmQj7cuT+BEISAJKD5aPak81kEguSUkTqd4JMIRkUq6EBG4NV8FExS0qFKkcgPUdPnzLVnla3FEXFnW4QWYWUEeorypKjk2NG43GU6B96MUlPIza+Al27wztDWY6BaOREgg2ljOiCVHG0PTIVY6rrXaQpB+do24bNdsvVcsWb1ZqXixXHpxc8fPyUvKiom4ab5ZbruzuuFkuavqesRhxdnHN985Lg43i7MZb1ZsPp2RnX6zVt28QButs7ptMpt7s1u7ZDkfHg+IhMBYyOwszewbi6oypLskwwmx1RVmOq8RzVaoqqZDKfsV6tCLZlVOV874ML+q7g8dmMo2nJi6sV+uaWo9Nzrq9uOH/2CZ+/ueP7HzzAOMPnr275zR98yPPnp/z2H3zNWmtKqQjGUfvAH714GRuXBB6dnDIdTwgiomKQSgHnkS4gPNjgUNIRcR1PJh0+xPMqlCJIOJpMaHuH9wYrM76+iQG3zGOfKFc+BRDIRCyRB1jbhdhzCYE0YXu4gcU7ZciAlISDFfxe/OC9aLKPMe8wVDncB+/+jG8fNuLxnQ4e+xMYAipE161DXY/h5Hhxr8Z0kJxFOCw9R+71QhVKuDieryRSeoYiM4TIZBX4hL9LrBPRVFtkQHSMF5LkhlYwn5/g8MzcMaZpWGzumM8mvFrvGFUl0/GY8WSK94pgAyEPyeoh9hYkHmd6MikIeRkRglTsBh9VtoNJgj4pmHhj9s5kzkV5v7rd0rSGxXrDq9trvrpasgU+evAQVZa02vDmdsndtuHy6oq6bXAIjvIxV1+9ZLveIIhcj7OzM65vlzSd4Xg2pygq1rs1m13LZHZE11uUyiLdPXh2yy1t29L3HQjBuCo5nUypRmPy0nC9eoMoJGo0RjSSxw9P+aUPHrJY3nFzu+CLyxv+/b/6m/zs65cUozEyk3z85CH5uGLTtDgE14sVd+s7/tKv/gqfvbpBO8+nX7whhCjyE7smEuNg3dXYn31JLqM2SVFVUXYyDGLTOcb2cVDQaozTUcXNe4RwjIp4jV0A0xs0glIpnBJMJzk/u1qxaVuyTNEYS6WIVgpKUcg8CTB7lBRRL0WS4PlEggs+ERbTICTpmg/rVQoGT0iRiupowxAzzoFYtm+uyrg2DoOHTKLL92o4IpU9A1R8ELG+4fGdDh77UmJI895L94bhpeBDvDPKOMouQhqWEwkZSJlDlh6DFH4mQaZF5X3s+O+ndBN7r+l7ttoRpELmg6dtJGKp1G/pddTu7Lodtu1Y+RV1rZmNR0wmk73ZlETGpqf3BJv+9hD20Ov+PXGYXt7XxM66feZBCHijsX1D1zXUu5a7xS1fvH3Dz968oQkZZw8eUo0nrNqWFzc3vLm+pshLnHd0WuMBUe8gU2RFSdvUGOfY7LbY4NnsdnjnePToMcttjcwkt4sNsiwYjyp013O3XrHebBFS0uuoOF7mgW3TUkxnvLm5iRBtoTg+z3j24VN837K5WzKZzAgOdt2WP/zqNR8+uGBbd5ycnqIdTBRMq5Iff/maUVGyaXZYFx1vrNaoLMPrPo0TeHpnAIl2gst1w+9++ZrxeEaRlUxGBeOyuCdK+ZBo4rFB2lsNSpEXkt55ikzRmhaEpNE9TWe52/acZXNGmeBl3TIaZ1R5RomnzInBI0vXWUYiWhBDn25oYiYvln25cVBakMrsgxvkfSPkvucXUuPjHvYfCvr0kncykAM2NUPv46DX9i1253c8eNzXZofncvi+OMg2hu8p8V51KQYhIEUmbQogB0NLwUGwyTg5EooglgHOOXa653pb44Xc63HI1Mp2Npoq4wLeGG5v36IQ7NqWqpokw6U8ds3iT00q4z5Ck3m0T3DOoUS274kcvm8QCG9hKHNkNKcyxmB1j2k31PWG9a7h1WbFjy+vuek809Mpo+kMbT31dsPdasWm7ZiisMbQW01WlJRlSWcNt3e3GGM4Pj6mbluc94gsWg5cXV8xP5lxt7ij2TQ8fvaYrq7p2haCwBhHUWaMp3NwDiEUXmU02nBzfUNvDdPjOUXXs/7qlt/4lV9mLBS/8+NPCcZwPKtYbgznZ4rNrqfKSxZNS2MtV9crVr3mZC7J8hE2SJ6cn3N5s8Iay8PzYz59dcnZ8ZTFuqbz8U7bu8Dn17dk8lOsdXzy4UPAUxUZIfjolJeXsWQNERHrdI8XsS/W2h5rPGXaIUplzGaKbdvjfGBalTSmZlZKCuKayrMoBSAhcgB9IHWohntRvEn4YRO/B5Xu6QURpYlAwC+ePbkPEId6vVHi4T77EHsb1X3JL94NVt+GoP7dDh7vQErDyU6RVg7RPKWBSMRw8ogzC0NDdRBJVipDKRuJY8RyKHaqo6hOFNbx4D3BW0LQtLrj05u3/GXznLmqUAKC7+MEaxZd3/IQNS+lKqg7jRMi0tE9OOvJx2WC5xQOQZIhw3kHWYZ3Didiahvd7qIi+ABROwkhaZHiHTYKUeCdpW12bLcrXl5d8vuffsWLZU01maFRGB+4vLnGebhZ7Xj6wQe8fv0a7x2d0VzMjrher7m6fIuUkr5p07zLOUIo+q4jBMFoOiXLctqmwxjH5atrurbl4fkF29s75rPjfYNX5tle0k9kil5rTHA46ynzjN26R0nJJx884vXVaxaLDdpEdOoPPvuaUgl+8PwJKs/5+vKWnfYEoWhd4NnJUfRgyQq0CRS5ZFzAR09PUSHKH2zvakIQFFKy6zt++voN06pgPKlQUqG9pxDRbElIRdN3RD8fhXexBPIEat1xVEV7zk3dsNUO1we0ynm72lAVFVar6JGbFRSZo1CSPIsewT4InMjiehSx7IAYOEgITByADPt1vJcsDANAkPaAFAlSFYlSnsqVYWI37oiENKZMW0TB6Gi5KhLsL6LoUUjqCOKesPhNjm+uu/5ncNynee8g4jGqH0RumRpUQogkePxumXN4vDMnENKVJJoyB2/wtic4E8sYb/DW8uXNFaumgQDKB6QxoHVERrJokmS8p9WOxjry0Zi260FIemdo2uhWr52NFGjAOxuXQogU/LZpsNYk2DWiP5HZGh8ED8Fh+hajO6zu6U1H03W8vV3wkxcv+aOXr7EyY3J6RGc0b968JS8KNruGohpz+faa1XrLpq6pJhOqyYRPP/sMqw3OWsoqNnrzvMA7h8oyzi4uaPuezWaHtZ6qHCGDJFcFWV4ymx8hhIzUeUBrTdv30bUtz5BFRGBOT+Z4o5mMp9zc3nF5d8nzh+ecTEu8KNg2DkUk0S1bhxc5R9MpnbXsek3mA+dnp1ytdvz+l6+RVUVVVKzbjmlZ8OjihGcXZxgXg1hRRqSst56fvrrksy9fcrPa0BmPDRIrFH0IdM7S6p7OWryQ2ABORIf63jpWdUuZleQpB6jbFqkEjW7IMkVZKObjnKqI+i25kigZ0lSB2Ku3x8UbS+y0c6OPT+J4yMP1KcW7nx+W6cRZJ3FfsSRAQO6z7HuCZCx3VfobQvobhBAoociSTcg3Pb7TwQNIw1j+vnk6tJ8ZIMz7k3UAfe+ZqcNjGOqKXzucM9EQJzhEeuCjE7qzmuBsCiiWy9slXy+WDPotKnXrcYFgo8JWMR7T+0AxntI7GxEQIbDBsV7c0u229H1L1/f0fY8xhrbtgECmMtq2Zbfb7f8+7w3Wabq+wdkeZzpM12L6Dtt39F1D1zQsVhu+urrjn33+JesQ52julguMMVRVhVSS+XxGXddRfT0xZ4+PjvjJT35yH8zSaHqWZVHAWcD0aI7MFFmR07Yt0+kUKSVVVTGZTOi6jrqu0VrvPXH7vsc5x2az4ez0jPFsSlWWVHmJIlpLWC/59Ksb3t7uOD+/4MHJnMb3zE9mTOfHXN6tWNSWuuu4OD9HW8/ZyQmEwK41NMayrRv6INj2gTe3W/7gi5ecXpzx0YePKUcFnTMgSqwX3DWaT1+95sXlFetty7bVbLShCwGHxAVBayyNsfQuoI1lWpUUeY72UfzxQYKfqyzng/MTykqRq0CwPZkKlJmkyBR5oqdHAapBuHhooR0yPGMKIIYHhzc29iX5PTrAPkDsS/jhhikOvHGHILJHCQ+CSXpN7EvlVFlBmf3rGjwGJqV3eOew1kZncu8YSHluCA7e4ZJZc4QbDcbq+DGJ1A4O9NZajHNRfi8YwMbOdwoWIcQsRHiDEIa6rvmXL76iabtksZh0Q6wl6A5pLZmAs5MTptM5vXNkmeT6+pLbt1dgonaotYbtdkMQ0PWGsizx3iKzOHpf13WklzvLdrPGuSjmG6ymbbb03W6fHdXrBavFHV+/esO/+PRTFtpydPKAk+MzpuM5mYoszC+/eslqs6brW7xzeG+ZH82omx3BWUZFRZ5nnJ2eMhoVeG8wuufpkyfUdcNytUIqxXgy4eT4CKM7irJASsFqeUdVFVSjiocPHzCbTBkyOm8NX372ObPxhLLIaduO6XTKuMpx3mCt4+1qxbLp6EzgdHJM73JeXt/RtT3Igre3S1SW8Usff0I1HuNFRl3XHI0KxqMpV6sd682OXCmMUfzLn33FPJd89PiEH3z8IZm3SbJPcLOt+fLVJa/fvmWx2bBuG5o+qquV1QgP7NqOznkaY9h1hlXboa1n0/Yx+1EZCsgJnM2mnEwrskyk+RdPlsWhuExF+UGZ0JL96PwB7uoT3B75Pg72RtR+cF8A3g0igtgLCX7gepC0b+H+F6b+RwokMhmL3fdTAkpFb6IsV5TqX9Pg4UP0VjXWYJ1Jcxs2oQ5xAWrj6K2h1warLbqPn/d9R9drOq3pjKE3NkkCGrTW9MZgrMU5jXOa4AwEFzen03inwRlEcHhn+J0vPuXrt1fgIuQlQ0BZA12D223Y3VyimobddsPlzTWL5S2jUUkmBOvtlnVT0/ZdVGj3nrys0kxOoO0brHdMpmO00fR9lOcrigKVZdS7baSiC2i7mrbZsb674/LNa37/sy/44m6FKgqMtmx2NQTFeDRhvd6xWte0fYv1ltF4zHQ2SdmMRuA5OzrmwcUDRlWJEJ6+a6iqIjFYDXe3dxgdn7vZLPfj5vPZhFGZMcoUs0nFdDqi7XYEPGUmOR5VNLsN0jmeP37CdrclzzM++uADrl+9jq5tQnJ9t2bbW+quJ89KHj54xKrpWCwX9Maza1qC7umd43pdg5BkWc7NtkWGjIvTY1Ztj3Fws1qz3Kz5+vKGxXpHMSpiNikCFsliV3OzWtD2HVobWm3oXRxOi3MnAuM8NkDnJYtWU1tPbwKrpqfuOkbjEUpl5Ah2zZZMekrl4wiECmRZZDErIdLEdsqC9wSt+P3BTdAnf5uwF/YJkLxuY8/jQOw4hNjHSEObSYVwzyANEBXnkl6NJDX3h/JdJEkAKeIMkJTfKgB8pxumIUBnLKWxZJlFSoPI7zvKcWIgifGKJBqb6r/oWxtAyH3ZYkxPZ3o6o+m1RqeHtwa8QYRUqjgTxVqcQ3mwBF7fLvi/fvpjnj95ysnJPJLZfXydDB4VokbDarujKkum0xmrxR3rxZJ5rriYjynyPFpJOkuWFwlm9jRNE5uf1uBdjQ+B49kMbTqCh6Is2e22jEYVuokox/ViyR9+9hV/dHlFLzMmo1hKPHz4EOcc19fXtG0bz4MPPDg/pxpNWSyuyYSk3dXkQlHXsVQaj8dJrRPysuDm5o5mW0eleRKk7QxVkXN2ekRT1xzNJpzMTyBTrDYbvDWM8pzjyZhJUUDncX1L5qfMp5Po1FbkUZU9+dverNZM5sfILKe1jkJlfPjRc0ZSIK1mqTUewwfzIxbLLTIvqEYTVrd3rJuaX3n+FLFr2GxqlBIEkdHqju3NklIpRkWJDbFfsdMxg1jvohZIbwy+COQyR1uDUJGW3/YGoSybpkGqHC8krYOm15R5iXUOk7JVJUNUDBNRPSwTgDwUnDrEA9O69lG5Lkq6yr0JtU+s46G3+r7s5rvDbGIP+b6j5zE4BAb2AWtAhvelkZRxPOJb8jy+05lHCAFtXBzLdh4fPCZlEH2v6fqOtu9p+p6207RtR9P2NF1P3fbUbRcfXc+uadPnLXXX0nYdXdejtYneJ2nQzHtDSMiLT+PTUghc7/lHv/97/POf/piu7gghpotBBFCC0XjO1a7l5fUteV7SdR1GW4RSuOBRyVC6burU9JVoHZW9mrphV+/imH1w3N3dslgu2G7j3VrIeLfdbRvMdsduteZyseKPLq9ZagsBTk4uCMDrN69Zrla0bQ2JYq07zdnpOXeLRdTsDHGW5+LigrOzM7yNwTJTkulswuXVFV3bMp+OEXi2qwUyeIo8ZzIqKXNFrt58YfIAACAASURBVGTsZYzLKC1oDY/PzjmeTMmkQATP6WyO6XpWqyXz0QgZPMvtGq8knTZ88PgJ50fHzMZjqtGI11fX/N5PfoLysFotyKqC9WqDM543V7cIlTGZTvFCRHHjImfZtPzaJx/y7NER5JER7K2FENGYqsxjUMEjhGLbdqz7jmXXJuRBsu5avBSY4HEBQEbmrpBs2h6PQskMKSXbrkZlklZ3TIsi2jwIRZlnkdUqQjQUG1DBtJbfDSEHQ3EDn8dH2ckhiziEXA92xMGgaOQkDRICPvm3eO/xLpbxQ3/Fh5jZkP6GveNc4D2s+E93fMczj4C2BuMsxjuUtdHg2Ubs3PoIN0XISRK8wIX4tUxTnsMFs9bEUfUUPOqmw2iT9DEiohGFY1ysYRPfQgQRYTcXuL7e8L/8k3/C+WTOr/3yD8irKEwsVIlzhsvFmrv1jsk8jpBX5YhCSHarO+62W3TXM5nNcNbS2gYlJcvFHW2zY9e1mACTasyjx48x2sS7nPEgcpwVtOuWftdy+faaz1++ZdEGmsZTjUsWqy1FmTOdTjk6mnN7d0k1KpAiY350RFGUyADjyRxrNdVoAkLQ1DsmleJoWiEpuLq95eGDh6zulnET6obj2RFlpji5eMCzDx9xc3tL39SovGC33XI0m/Hs8VNev3qDNprpZMy8GlHOjtg10WYymA6CZrPZcbvYAGAQzE6OOT4943a55vXmmul0ytvbG1y3Yz47Yjoe8+DBQ15cvqZrvuYv/8avs97ssMYzqyYIB7/7k0/5/icf8PDxY9aLDfndmiAlxjp6ZymLnCLLyLKM1jiaXjMaj2i1w1rNUS4Y5YpVvUU7R6kE1tlE4suwJkDmORqPaF3P+dGYzrdUWSBXDikChQpx5kZ6Mu9QIjYsB2IXkISPo+WEwu/LF58yBblnjf48SCATzPrOmL0nspa9gxDXrhBR1MgGi/UG720svf2A9AmkDah4z8EO/kDf4PhuBw9CLC16jc41QKQUyziY5LxIKt6x/rODxWOK6/6gsz2ULn2vo4J4F0esIzPdEXwkhe2jdwoeOJ96LBa85w8/fcl/X/5j/gPg+588R0wKpKyou5pd33M8P0YIiTeOr6/f8MHZOYSA1YaQ52zqLXmRkztQRc7rN2+4OJkzmc3wQVCOx3HQjcC23nGclwiga1p03/P65o6ffPU1rxcrquNjzNU1Z6fHPHr0iNu3b7HWsl6vmYwnBB8ifd471pslQnqqKkMQEZXb2xtG1YjpZMbjRw+4fvuGJyfHSOGZjjKMkSg7ZVxUnGQK0fe8/fQLHIHTyZjWOMZlyUePHvPixVfkQTOrFNMi42Q8YVnvmE0nGNMxUhnteouzDiUjAjSdjnj88IJ13dBtl/zg+WOWdcPt9TVHswl9bymKKtLjVxtGVcntYo23jlprlHE8e/KEn335ml37ggfnE06n56hc4YMkywtc0ORZjvex/1XkCm0tve4pydFYhAnYAta9oe57zqcTjPXMxyOsM9jgCE6wbWtOzo5RmeLB8RFtu6JQgTKPPzdPQlT6kKcx8DCGLOKgB+JTWfOuTKAnJJHjAaH5uV1xiCSGeyX04UWD0+B9huLfec1QJkV1sj8fAeT/z48QAlobet3T9VmMnFHbLQYKF2Lq6UGHQO8DJqRG0nDiQtincM55cB7T99heY7WJHWlC4lyEhEhEN3dCQFgfsxYfFcpVG/jdP/iUdtfz7/1bf4Vf/9VfRow8X7y9ZGMNeTXBGsOmbnC9oek7To6PEd5RlVX0bRGCTb1FrzTOR9nAV9dLpMqRMkeJQNfWzGbH1E1DmeWIIufV8pbXiwU32x23u4bx2Yzf+NFv0Oqely9ecH56Sp7nrFZLlBScnJyi+6irIcQIKeHu9oaHFxdRMHg2ZVaOCHXL9VcvkAQmszG9bfnhx0/5+uVrxuNzyjKnlIFMCi5XPR8/e8bR2Rlr3bFtdwTVcTRTzEfn3CzXHJcz5vkEEQSdyJDljHGeEVQg7wz9SSSVSW149cXnzOYTTmZj3t7coLWhUBKtLUJY8mrE7e2CWbK/fPP2hmazxQvobM+nL17EEXc83itulkvO53O2neOu2XI6nWN7gzWeyXSMULHkaGqBMjlBgsZxu2nY1A1CSurM0tueSVUwGZVsjAEUvYO+1zgROD+acWVaTmZjZFiiomnpnn28708g0kzKuxOtgUFNjKgYd7DBg0h9vPd6HXIoMQ5uhs66PZDgM4UizkwdUhSc82n9RyQv8omSJuz7s/x/iuO7Hzycpu0zVJZhhhRLCKwH4+KMgguRjtw5j/axnIn1/vCIHI8QYqPI9QbnNXgXtSclCGLE9nbghMQLgPOYBAEL79DBQyv4w5+94Gaz4d++veHZ82e0QfLBx7/McrGB4On7jkcPL9iul4wYcXEWYVzrPZvNjt16Q2t2VAG+fPWane6YzU5Z1zuc6fHGM5ue4Ans+p4+eCbTOUKAdQHtLJvLS371137Iyx+/ZDaOvAvrHUplSBl48fULRmVBUeZcX71lPJlEfU9jabY7To+PUNowzyqOxlNQMJsX4HpOsp7sbEKl5pTjCRdPpzw+nfHF1QZZzLk4fkjrNOPzKeNS0m83SJnx1dcvcbVB1IZHfY+cj3n+ySN22yt6J3l9ucB1Gm0cre2YH88gGG5vNkgk01EVbSG2NcYGZK9xLjqzeePQVjMZVcmoSbCrO8o8DqOtty06eE4mxzinEzFKsq1rRkVBpjIKlVMVcQAxyIy62ZJnUUFsUxtO5iNciD22xa6lKiznp6dsup4PpmeoUoEXSTel5vHJCZkY0+ptJHuFCA0H5wkurinlRTRT97FkEakZ6slwPs6yBB9QzhBc1CZxIkoMRCjXR+uPBOOGwSfZ2VjSO4dxDqUNXgicszgTZRqNdnGf2NjTs0ZjfLSckEJFNvA3PL77wUNbemmQosO5aNgUAOs8OgWPzgc64+icQ7uDWBoE3ov7dI2oHuWtRTgH3uOFJGQiBY+oD+qGEiYZGltno65o8AhkTGMNrDYtv//iNTcmTpl+/4e/xtF8zna9iqrmzpGXJdWoRGWK7W6LNpZFveXq5oqH8ym11izrGuM8ZWV4e33NdrXi4YMHbOoapKRuO+azOUrFyWCfSbSzZMWEL774gs16Tdc0nD24YLPbUaiMZr2Jzbzg6eqGcTWibxryLOfy8pIykwQ/QeXw6OEozVKUnE7h4YOnPH36EbvlFd3GMpt/wOOPSorjh5w8syg1ZXW75cOnv8Tpsw/x3Zp2t0AgOHn8iKs3N6w/e42oCj7+K38J362Z1zPq3iJGMza7HV+/esuzj77HZD5nefOKu3UTxZTynNJq1tuebd3QOU9nPM44JnkGGYTQMR4VVFVJpw1Hx8e0bUunLVlRRLc2pRhnOevNOsoZjEZ45yjLaKGhiaJMPgR2TRS5dsmzttE6ynz0mmo8Qvc9VVEQpIwN4RyW61usNey6hqORoErCUNo4tAVtwbokOOQPyGKQ3FqiZoghuds7j7Qu3qwIGOlwIaQAEtfqfpTCR86TNRptNLrPyaVAhSg/sS/1tU7UBPMO38kYEwOZk7+gLPqTH9/x4AHWeox2SAwhJHUwBMZ6ehtd6Hsb6KyltTECD2iGFIroNTI0oKJRNENE95Hvb31M32SINZAdgoePgjuDiGzsXMV5fJkpHj16yPXdim3fMp1PebR9jgiS1mqOTk+oAsyO5sxySS4lLgReX71l09bMqjFNpxkVJbPZMbuuZ7XZYPBgPDeLO9qu4/nTD9HOM85Lgg8URcFoNOLi5IyNibT2wWzZec+2qTk/PmE2mWJ1hzM9eZLhi5aUPdZqRkVF09aM5lOePHvE0eyIbt3z4eNjHnxyweOPf5Xt1VfsXn8JqmL6+BnZg+9TmR7XrMkryfjxGflkgguGER6je6SqOT6uaCeBj3/9R0yfPGP16qd4N0OGnrLacXxUsVgWnF08xKIQqkAVOTIYRCajaHFwiCDR2tFoQyllHFwPgegqE7VHprMZQiqM9VRVNAnrtKbRPQIwWpNlWaJuRxas8wZjA3rb45zGe0vb9uR5jjYe65JGLJElPBqNqKoJX97eMJ+OUAoyochVxqreETxURQ5B0GvojE8BJGBs0oT2AxQbIVoXAjrElr4iGa1H1iMahwkxizYJPdk7w6WS2pjEV+p7+kyRKZFEj2LwaLuWvuvRWmOMTpymoSSPREkp5R4Y+CbHdzp4gMCagBE2DQD5pOwV+x3GeXrj0M6jjdvPV0Did2AZsG/vHCTJOUIU0REIghAoHyE1l5iAkdHq9x+jCJCPkG3qjVRFRdNs2TYNWX7KZtfw45/+lIvzc7Iip941TOZz6rqhx9NminZXc7taIIRgMj/hbrfiuJihQwDjWa5vUKViko+4vF1wNHfk5YJea3bbLdJ6njx5xm2n2TnYvV3s6+BG90yt4fmzZ9iu53Z5x2RcMhvNuL69RfrA+fExvmsQQrCrG+IoHlw8/ognzz5ku15S5YHx2TPc+Iz5sxkQkKGgvPge1fEZuq0jUlTkKOlRweEIFFmJt55CFVjXkVcdk+MJrt4gbXSYy4QkC4IqLxiXJa7XWJEBCjx78l/X2TgYaD2VgMm4JCdq0eZFjlSR1NXrnnJSIIiBuWm7aIche5z3SVQ6qnyV/w93b/ZjW5bnd33WtKczxXyHvFlZc1ZXu2V3G1uNWmDUbQbhB7CwZQuEkAXyIxJ/gXngBQmJFySQJSMBD7TAQgIJISFjxjaTcdHuRnZ3DVmZeYcYz7zHNfGw9jkRt9wDnSXTpdqlyIgbsWOfqH3W/q3f8B2MoMwUwVlCdEdzLucdWWZwMZIR0Fpyks9obEuMPoEB85xd21EVBZu25oQCIWSaVFhPHQNNOyCFhCjpbaSz0FnoXfo8+IALATEGBBdgiGJ0CAThHFL7ZB0aI4MYhwIx4saJYBTglUtSDDaRMTtlMCKNxoMxCJE0Wdom2W40XTvCBoYEsLTJhjRxpsTIo/pix0908DjI/6UoCRBwLlGVBx8TatSFBDW3nqcZWGScnT/pYuMcYSQJiQP1XUhikMdfisSxXvXj7P0R65Gb7AiFDzGw3e/Y1TUy08ylYrlckueGP/ZHf55mtyXGwL5r6eo9i7JAxsTRaOuG3/r0E8qq5M7s2DY93gX2fc+HJ89o+g6PYr1v8NwQBkd5ecFkOqE4OeXq7JzbzRZrLX3bjaJFluVqyUcffokf3HwPnWlMnlN3DWWeU0hFs10nPQgb6L1HZRYdPTf3D7z8+s+gy4ANDSKb46XGR4M8/QhbbyCbMgRB1DlkJ8g8MDRb8mqe5AJcYiibIscUJzjb0O7vkDODMDlhaEald4NWBcPg2C+XxCAZljtk7ZCdZ3A92gVO85JoHicEUgqyLOE4nPN4pZIiOwd9jNEcykusdTibmuGToiAzgkmZsZhNEAS6zhNIY8qIoOsdUQimZY4IFusVmdKgNVFpXt/f42zgw2fPWDdbOhXIlGawIRltuSQiJAWEIBmcpLPQ9pHBCgY39udcRPh47IVwIHLKkRXrPDiHk4FOSIaY7Cf8Yc0JiH2PVZK+07Rao5EoEVLQGUlu1lq6tqVpOto+eRIPfY+ziQAZk53gOO79qc08SG5oI/PVuYTVR4D1IUVzH4nOIhOTngND8TBpUQdocEjXiD4eR2YCEDIgSJ4dcGA9pgdBIkaqvDj6wBxGuC4kfKsn0vYd51JRZQWXZ+dsNiOoSmusT6hYZTS79ZqqyLndrtFS4DvHu/aOspjysHwArVjVLcv1hulkinOez25u+PqLDzg7PUWWOfXQobTm+eUV6rufHxmYSkqm0xnX19e0bVJ1Xy3X2K5lUZWUmSErktanwzElY7OvaYuc73/yffKqYDE/p247qvMdL04ucSGAnNE2t2TLNdWzCdEnF762dxg5xY84mBCgtw7bO7Qs8R2sr98yF1OG7Rq33+OaHretUa1laiN6uyPYyKTruTAZxnma6MmjwEmJC8l0KcZ4lGCQUlBkBbu+Qwtomz2+3jOvqpRR2YSq1SOuQ2uF1skiQY5oTiEEg3XEKDASjASl89Q4l5JVXXMynZApw2rXEAXMyvLo87Pc1czLHCWK5IjXDygZj1OV3kY6B4OVDENksBFrI96B8hEfEmU/jNgOEWMyg1KB0Du8VgzC0sdE2kvZh8PFgFQeNSriaaXQSIgeNwz0WiMk2MHSdwNt11E3bQJDjoRMNzb/f+o1TFPm4XAimSMn21s/BgY/RuXEBYgjao4DQxFGP9D35e4P11UHU+xxJh9CGH9nfDNHgJkWMtFoQxr5Quq7eO8YnCQvci4uLvj4mx/z+t1rdvsd1vZkWtKrVFO2+5qr2QwjFdvtjkwqpFJc3y8Z7MCLy6SSZZ3nB2+uWRQVVTkhxPRAzk9OuN5vmMg5VTFh37YoIanynP1+T1WVxC7BhdebNW3bYrSG6AkupeJaCV6cXpIbgw6C2LsEhJIQljWvf/N7vMk+5ZM3b7m9vebP/PN/Hp0rmpt3/N1f+zU+/HjPh1EQh5bd/eesVlu++cd/GWclzWqFdI5+u6PfbGlub3HLwP3+U/zrhq7eYPs+IW594KS3fOs8jYud99xKx2AbZhODHNI0qW77xBcxBkjkM4RAqTTqLmNyjjMeotQsZnPevHuLCxElNVWZY60lMznGCDItqZsGPZLH2n4gBE+pIovTRVpbUtK5AZXltD4QB4/JUwP2/OSMIQQCis1+T+sClS5ZLx8Q0iVhKeJYUksGfwgcYF1SFQsehPOYOAosE5BRwPg3K2HHQCFxSjAEsFEykO6TCx4hJS3jhjZm0M5luDxDq0fFub6ztF1H07U0TUvTtgz9kBT9DzB4fhw1j5/w4JGyUY9zkfBEDenAUjx0sf3BYTyOkWCcj6fbm5B6cvRggfFn7wmhJJ3rdO0kc38wZFKIhORTjxBjgQCZsAVaac5OF3z29jOikrTdwHwyYVIVfP75p9h+4PmzK5b7HV1T0w89H149pyPwyZtrCCRPlO2W3gbOTk4plMSYnHdvXqPzjG3dEhg4QxGG1NFvO0s9tGRasd7vyJRh/bBicXLC6ckpu92G+XTC0ECZZ5zMpyymE05nMy6mJ2A9tk3yidOqoswLQnB87Wun6CHj7f/wtyjLDNvsOOk1+mbNqv4ObmjouzU6at7t/zuUkPjtntAk2wfrBnw7cCkmEBXxeokOjkwn42yLIxY5WWZo+4Zt3ZFnSUk9WovRirYf0CLnyDUV8ehzG5C0XY9SCYzWtA4bFcEnPdckDSDJjGRaVsnkXCVd1b7vUSTJQRcC1llOJvNErHOB5yeThGAeG/Ld0JHZgSIreNjtWG5rNtuGYXAsFhOmZca2CQiZ1O0hiR67EHA+OVo6m8CM3j8CtFwEJyTusO4iKBzKgxMeFwTe6THrEFgc7gAdEKk/lDbKQHADdijoepMCI0nGYhhGCkfX0Y4fw2AJNk0Oj8ePkYD8RAcP4BEdd8gUAEbq8vhViqIhjqi+EQqMGOvhQ8Bh7FiLkXSUriTGBuqRsiwTwS4FIFItdEQJHjgLjEObxHzt7cC7+1t+7ts/R54VdINHKovQhkpnnJ9fIryjR3G3vueHq1vOp3M+uLzk7f0926YlzycYNZApSQzw+s0brB1AK37zez/gwxfnBOu5tUv2Q8tnN7dpdC1l2lG0p6t7+qbj5GSBMQqC4+L0hEzD6WzO5ekpV+enXEznlNpgmwHbpJ1IIZhOTynyHCPSdEg6IJtz9mKRYNW7GjX0aKvQWiFWW/xYMioLrrXJ91Xr0f438WWklGmCFUZQU3TpoRaRIpNIkxOVh71HS4UrNZ119INDGI3OM5p+IOgs9bisTZlk8GRGYHvPvt5jTLJacG7Ae5kc8OIBiRlh5K+46Gn6jllejOl7oMoVxEhuMqTS7DqLi46Lak49JG3UbWO523RJCU6AkpqmS9QFqcZ1F59MV7zH+dHv9gnpLcbUb7HAQWFMhoAIDm9JSv4ijMhpgWds4MckmuxGjx+cxw89Q9aPE6VRrd37cSLjjhMZa5OTH2GUwjw8ST+1o9oDCk9EiGlycjik+B0Ma1IkSQHkWKY8Sc8OiUk8fB0fLxnTWeIQ1sXIizm6TqfjEDuSh25ixNb7mouTC0SAuq+ZzWdMZ3PaviPThuVmi2tbsuC5nJ9g7cC8nLLdbAlE2qYlNzmTacXp6Sk+Sr773e8mcFrXkSvFw2rNu8ExLadYN9APllxnvF1eM68m9N5DkWpo7x1Gg+s7RJExnywo8oKyKMmyHJ0XTKYzqosc1ziGtkvTJC3J8wyNJCsydGaOJszaJDZs3LWEweFFElCyfU/dt6A9qpAYnWH7nggJO3FQZYsQgh+Nn2VqjEpYTEqcG8hUSaFIvI4IvQ0ICQ7BZojYCO0woIRiMZvQ1jVKZXzysGTfRoRQR8boQQ1tGPEMITqenZ1xt3pIU4lxXJqptPyrIudiOqWzHZaA8o7eWk6mFYvpnH6/J5MZl/MFman44Wdv2DUDZdkTkXTDUZGUZKqUNDfiAag4BjBBEl1247k+HhT+01oX8cB/IfGsxusJUiCKCatACClCRe8JVuL6JMYU5SF4pHGuHzFKzrlk5RHjWJI/LuT4ox63f4DjJzp4pCxCjTh98UhWk8l1C0g35L2CYsR5cIABP2YL7xvepGuK927eIdg8NpT+QdLhuFPISMCnMVqMvLx6gRCS7XpPrtYIJFqVrHZrzhdT5tMpN9fveNj1vDo7ZTHJuZyfcLfa4EOi6J/PF+Ta8PnDHbPZlPruHiUj3jqu7xNgbFt3iOAoJxM6e0eZZSyqKW+W9xQmOc4pAZUpMSrjpCiZlwVllhNV0lyVWiQ2rM7IioLSlqnhPKZYBzyFUhppNFJrTFEA4PMK2zTge2LXoYJD9jGJQ5eKyXRG1zYMQ5tKDg9ZlhzvhBBY26ONYYjg48CszIhREWJF05c4FQgugtTU/cCmczSrPbZxeBexccD65Kq3aVu0NETaRDAIAlwgRknTpYwqM4rSZMymU+5WD7iQGLeF0igt0TJihCDLK+qhSwpgLlCY9Hf7GDBC8+Zuzb7vuVnVOAshOG4f9glX4ZOxVAx+JJul7AEYMULyuGHpJ8vNHXalw/fGexQFOHFwvE8nPHKtEpCMUSTLS4my9phhA0fPmQOm44C0Tuv5cVMVTzKQL3L8RAcP4JgRvPetePwBMPY6xpPfSySO58f3vn40mH7kDTxe7PgC6Z9PAs/7QSjN59OiDeR5jo+Bs9Mz8rJkvliw3W7pu57s/JSiyFFKYUyZkIUu6ZIaKZhNKmyAVbPnxbTCWosPEa8km6Fnv92QF/k4Yo5cLWZ0TcNq9cCL03PW+x2zIkfKgBiGpE2pDblRlHnBNCs4m85AyiRI7Fxim04qBJJqVuG7AYFOplhCEqzFp6cEGQO23eEGmxauFAgXUVohnWJSlkQ1tpjVmBUOQ3LYE5IkA5yUslSmMUpSmQQPz42gqDKE1Awu0LqBVduzXnf01uJiSBlMSLOtTEm01Kz2LXfrGpRGK5lwHSOLte97YkxgOh8ts8Wc3X6HCB6JYN9aEILBWV6czcmMZts2SWckJijhpJygdZbwH1kqCYKLqDBADHgvqGv7qPT1ZJ0GUrZ8LKmf8EfsGCDe37SeEPYPAkKCo2DQ04V/2AydC8jg8U9kOJ+u8cPvHfx94o++3GFN/zT3PB5dtZ486DHNuGI8JHXpOASFp58Ppz8NJ/EfuJOH67wflYkJYXh44R99I8dNJVG92xaVGb786gN0ZpLvSb1DS8lqveJNvWdiDNIHptWExvXkRnEynbDcb8l1iVSSm4cHlvWeTBeYouJiccrDwwPr7ZaHzZJJVfH8dMHF4oQvvXhO3yeUahSe3luMycgyQ2M7bJCchAkDgW1b4/aBV5eXqBBx1jLYgSLLsLZHCchMhjQGnWeJhOg90Xkk4O2AioJoUmnh3YB3HhsTRiIeZCLdkISjJWRlhSoKXLOjKnOETJBwKSN96BFFji5zXIhs9zW7umOIkXcPa1yQPGw2WARFbrjUhtW2phss2miKLKFFk9G0SvIMCNrOHt+iwQ6YTGHyjLc37/AuINVhrL1gv19zs2yYTXLOT6dMCsNiUnC33KRRsMlxXnC/3aEJfP35BWWu+e03a5o60dyP25V8DBARASFB3x81Scf1cyxRBMc65TAFhGNQ+R1bEWOgOqztRNd4DBQ/mmG///z8yIY6/uenNnjESKodnzQ00zFOQI6RnvHGChAJ8nt8O46BQ/zIjXosS4705EMoOjZYQf4uegejr1wic1UV22aL6tPt7IaWF+fPOT85YXl3jRSR7202zE8uyGQy3T6fnqJOFe1geXX5nF/7f36DMq84nc64mp3yyc07qumch4d7qqzElo6bh3tiiNRdizKaSZ4zzTOatsc6iwkmean4yLOzc9zQp5Ao4WazQQvJ1ck8qc0D6+WKWVXhup5CaOYnYESFWUzIyoI4WGSI9NaiY0VsuiQOLQPGaGLdoI2hrvfEGNl0LdFFKpNDpRmsA6VotGTrLSamjKU+CvI02JhIb6eTCRFHOZlSW4ESPvUTeovKc4LvOVtUrPYN67pFScn5fMK6ThKLXsDgPF56qiIxsJVUvHrxgne377CtHXdkx/l8zmJWsN9Fahvp9h3aNKy3K6oi53Qxpe56zuaLlJE4DzLynU/eUPchITNxhNFTRfBEcvDJmhOH51Y8PsRPBoKIIH4k4UjB5KAUdlxpx9Zd2szi8TridwgUj8tbRHHcFA+E9MNzdQxCv88z+HsdP9HBA0YcBzwJxe8HkghHo6dDkD1YK7yfYRxqz4OWQXi8cccpTYoYR1euKDjyYd47IpFkvpRpgzEaJSK9HXh7e82HL54zMZp92zApC1b3d0wmEy5ePOP25g3K9ZSh4BWprAAAIABJREFU4ETlXF6c0tQDk3LCMAzUbctuv6cfBrqHBwpdsG43dM5yMl8gJBSzGQ/bNZOioNvtmU+nrHc79l1LVZQ0XZrpT4oCpQ37fUdEcD6r0Eaxa1vKyZT9bk/bdpzNF3Q+ILuWXCq6zZYp4No+YQt08kpp7EBX70ALgnfsNhu6vsd5x26/T1oW3lMvVxRC0Q2WbmgxmcIy4O2QhucCus4yWM+6a8jyjOX2jllVcJHNeL3bMzXyeKfXmw0BKPNIbjRlZmh6y3SSs6v39NbSDYHWOYwSOB/JyopXV8/Zbla0TYvtezIjOV3MeHF1zs1qTd17bByYTzOyTFOVFdYOdH3PpCwTMc1HJuWEtut52G9pWjsytMNjIIgR9d4yjU8e/bTA3s9+D3ADngSKQ6eOcd099jyO3KrxBeLTsuN3e/rjk4z5uCGO1zmUWuLpX/oHP36ig0eMERfDYwnBSIx7kqbJ9xzingQB3k/jEgX6IA4UCE9EUMR47rGBFB9/V6B4nNyMf9d4w6WAyWSCc47JdMG8nKSmWIDd8p6epAWSG83z87NESKsqDBYXPLoq+agqePOwIUpNsDXCZBhleH5+QTs4nI84LLMix28cL14+Y7XeooVAScF8NkPrjG3XUlUV2kNZVbgI27pJNgnFBO8jgw18en3Ldbbh9d2SxWRK29XcTVfMZ3MWPpJZj9jWvPnsNZ7A/WZFN1iqaoYUkX63o653XFxeYu3AdrdFKsV6vQYE7eija7ue1iZP4EmRI3WyNDBC4mLkbr1hVs2YzE5ZbZes1iuyjaYPimbwzMqK1f4eiSDPkqud0poiRqyGbZOkIi9PKh52itZ3RKGYFoqPrp6xd453y7eJSWsk3kGmNbPplHerB1a7BqE0wTtm+QTvLeeniYuUaU2ea6QxuD7gLFyvW3qvkVrASJlIEn/jZiTiYwg4KAE9aYTyZI3BAXf02KVLmKTfpfQYIUnHdX8IPhxwSe9nIIfXj0/MosQhUMTHoCOE/J0mAv+fjx8reAgh/g3gXyPdpt8A/hLwAvhV4Bz4v4B/OcY4CCFy4D8G/jjwAPyFGOMPf6/rR0iCruKJ9+YRlpEg4/Jgg3CM3KmQe+x7jqKwjHL3hyASxXu7x4FF+RQ89ogbOZybTj7gPUSI7LZbpvMZ05MTirwgNxm5Vthuj5MCJyT7pmZWlMwnE5puT9P2zCdTQgCrJRfPrnjx/ApzdUaM0N08YPsOgcf3Hcv1irKY8KUPXkH09E2HyA0+ROzI//bRMysLXO9YrrfMqymT6RQhBTpTPDwsk/ZDnHOuDG0/UJgefehX+MgPb26526z46PlLdIC3d9c0NlkODO4Oh0M6z0lV0fUDdd9xu13i3EAEmrbDmJLNbof1lqZ15EYTpSdzkn3bEIBXH3xIHwU/vH6HRmCkpJjMaOqGm82aZr/F9x1Rpp6LjhIbPPdty8l0QiEE8yKnG42wMpWMjQotUErxbrmk8Y6m7SnzDB8jWW6QxtD2jv0+geO08FzMJ1ydLViuHtAiAepyY3De0uPpYxImiianMCU4z+AsvusI1ia5Bp56r6SFd7B6Shvcwcl+dDocm5xRcBybplUmjsGEmKYmh+whfX1QHePRGAr5uPTHYJACmDwW4sfndRwQHLuE42j7ix5fOHgIIT4A/nXg2zHGVgjxnwF/EfhngX83xvirQoj/APhXgX9//LyKMX5dCPEXgX8b+Au/3+sc6rLDm3CYckC6MUeVdJ42SQ839pA0JGHhMOYeSV3sYGr9eP30/4tj6SNiehMSnX+M+jGgkUiZIMaiyOiiA20oy8Sv2NV7mvUD1XSGLis2+5o8y8mznGenF7iiwkhNiKTU2Q+8PD8l2p4gJPveUbQFdXdHFIGvfvCSh13DJ68/5fLsHACpDMv1jvPFnME5JkXJLM953d5xsjihVIrBWzqveLNaEoKj0IZ+GFjVO2yZk1nJrCqw0fL3P/s+RVbx7PyCh+UD3nl2XYdzjib21G5Aa0FlDGaS0bgNbx7u2O4bRPBMp1Mikrc3d+zqmsvzE3pv8THwzMzxfUtmFNu24/XtNYvpnG994xvc3NxQ72sKqXh5dcnd8o4Ykw/wfDZhGxq8S0rrSOj6nhAFWkQqqXioOxaV4d22wyiVtC+M5GK2oKk8u82OZuiocsViUtLbgX3XIVWkEKlhLUJI8g1C0g4WGzxXp+fcbBp8FJSzBT5zSfbSBbADXhhcrPGj2HCyLk3BIcaAGu0XZBRE+Zh1iNF0/WB+noLJQaLwUTYTBDImOn4QJDRpCMdNTIiDAvq47knavWLcTA8kjfR8iGO2Ep5kKFKIYwb0RY4ft2zRQCmEsEAFvAN+GfgXx5//R8C/SQoe/9z4NcBfB/49IYSIvyfELek8KikRWiWT5zHyHt2wlDxG0nT/wxFpBzI5lY83V5Kguyn7CEd6/SFypzcwHMshIdO/Y/THtFAjCCIQjeLq1Qd865t/jErntK5lupizWt1zt25Y3t3yUVHw1YtnWB+o6y2/9f0f8KXnz5lWMx42SywpAM0nU4SA1jpchKurSz799A1N05CXBSo3DGuXhGv2O6bT6cjbyOiHNDVxwWOHAYdgZgpiTG73dT8Qhp6vvPqQru242224nM84nczY9gM2JpDay2dXKBFphhonBLebNd3Qked5UnHPDFlZcX56wnK9QmuXwGBRILTBZAXvfvAZTW9BKYoy58OqRBclt/fXlDqxXaXUrO7uuHn3lsVshouRpmsYukjfSKyzyWay3lLXDdtmR2VyvHdorUmdPyizjGXdYlTOSZExKyz7YWCwPZUULJdLehvR2iBIosBt1yOB5/MpymhcCLR2YE5OFIpd79nua8pccnV2hdQZs6oCldOrgAgJvckwYKMkOou3A97ax15HfN8pLh0SJdL6FSrxmpSSSKWfBA84jHQfdXQ9yPAov/nEGwrBY9fumD6rcSEzBqYUOJJvrRqbtOH48+Rj+4cQPGKMb4QQ/w7wGdAC/y2pTFnHGN142mvgg/HrD4DPx991QogNqbS5f3pdIcRfBv4ypKCBSubJRmukGoPHyIyUSo0+tY8d7tRoOgSCFEAO5YkXhzPSLN7FMPY/DsnLaBIcI0FERHzSYI1xNNERyGnBH/mTf4I/8vEvMC0X3D+8w289PkReX7/h51694vTVC+aLGUJETuYntH3L9WpJ07aczWasux2zrmSaFWQqIytKkJLlekOuQeWGq6tnFJni+uEuSQBst5Tn52w2a7IsSyxZJdBR8bDcYLQmMwVtP9B0HS5GJgbOTs9o+oHoAs9mZ6hMcrvbUkjJjRtwPtC4jtzktINnt2sosgyTKVwM5JMJpqqou4a/8/d/i+12hyaNGhfzOUoKlss1DoELgTzPcMFjNLx5/RlSRApdkWlDkVX0mxqUYrtdszg7QZHsP/dDQGmD0ZpBSXpn6ZynzATTssTaHo9k3/RczAxaKjbdwOe9xWSKSiiUKsiUYtsNNL0lG/EfmU7TnyLTKKOw3lG3LS8vPySGBOxa3a8IQvHVDz6gdgFZVng1QaiMUiUmt3WBQRsEEWE7XNPiY5IdBI5cGhcjmtF8WiiQCql1cp3Th4/kp3vMepMA6lGGwDmHD0nfNMSA8xIxCvocihzJCJ4UYnSMSwFBHOwnhUQInXp3PPZNDsxjpdQXDQE/VtlySsomvgKsgf8c+Ge+8F8yHjHGvwr8VYA8M1FqhdQSnSV16kOnW4h049MfE0aZtjGN44nhr0jaGyEmXD+jI3kcSxYXwziPlxAjcsT+iyiOxjhHtWkhyCYVf+qX/wn+yX/sV5gXMz5/80O+e/MZ211NHHr84CiN5Ksffsi6Hrh7uEMJQWk0n6xW7GVNJg3PL5/RdQ3bNuEJ6rplMsm4vDpDh8BuNudhU9PUHfW2RsXI8+fPWEymuG4/ZhuSl2fPafqebvDgLPfrJVErpsWU0zzpVygp6fs2CSlryWa7p5pMWA890zIj04ZN3SOVT8HTKBrb0bcDbTfwC7/wj/D67TuGpsaGiHURpSUff+vL1Nt9gtfnmvv1GqUMV5cXvLu+xsiMxbxAykg39Nje4UtJ5wJDsGQZfPnZOZ/YgXpv0VmBEEm8Zy9TT6cokmn3rJQ0fdoYyizn8/sN06IgywSdhSLP0EajnMX2LhleA/3QM8lzdDyopls8ESUVF7OKSaa5WW653e7xPlCWGmFyvCqYn1xSu2QkJXxE+YBwlmA1JgSE6XG6YxAdEjf2OiB6iYhp4zv05o4Wj6pAZRnKaIzhyPJNDvcpq042owGpNTa49JpREHwkOpAuYUgQAj/W2YfsRSJG2wcNSGRMnjMIeRwjS5GU8JRJweyLHj9O2fKngU9ijHcAQoj/Avgl4EQIocfs4xXwZjz/DfAh8FoIoYEFqXH6e/+BWmOMwZjkvfEoDiNHu0aIJOEeRqi4kIdabmw2BU+MCSIcDiPYMTEJYw/kQKI72DXIKN/DgEQiQgt+8U/94/wL//Sf5dn5gvrhLQu3p4yW7z7cYKRiWs7ofGS52XG/31PkM9b1jigEF+cXSBRewG9/+gnGZDy/vKIP0EVPFgJVhFwqMiOZlAoVJSZT5DKjaZqUfEqJynOUMkyzis/vHhBCsumS5OCzZ5cYmdP1LdZ7+hBAaXZdx/1mQ6YNSDOWS8m+0wWPRLHdrGntgPeOeVnx8Td/hurkhHy5pGn2yd0uJt7FYnHODz99iyLSdR3VdMZkNmOz3XC2mCMVaC3JpaRpGtZ1za7tefnyFc32ASUs33/9ho9efsh3fv03MGVgkmmsHQhRJaElEclkxDqPVIrWRm5XWzad5WyedtC2t7TWM7iAlJowWISAPNdY5xmcSw+xSbuyCx6CpywL2sFRtx3t4FBEqjJn1XZczC+QpqQqcgYfUCGxdvEOhh4bIjprQGpClLiQGpE6MDJzgXFNHdaqMRqtMnSWeEPagFSplyfVI+Pbe5dKFu+IQSKVwHmPVoIoHF4+IkOFSJgnKVOprVFIEkpYRImSKtlTPplSSilTFpQZtM6+cAD4cYLHZ8AvCiEqUtnyK8DfBv574M+RJi7/CvBfjuf/V+O//9fx53/z9+53pBuTbrohy7Ix8zg0jMSoEg4Bl9S/ZOpNHO0mSfVnCGIMHiMZaZzgJEnkp0NYUj2o5HEEIxg1UIEvfeOb/Ol/9Fc4nZ/Qbpd0q1tsuyGTmvOTC3yICAWdC3xyc4NRirKYUVUTtvWesihQOqPUmq7VBDtA15Jnhl5KFicLKh+IEurP3vCzX3rJ9f2SQGSz21LXHikEs+mcpmuoh4Hv31yzXO2Ylzkvry4YvKf3AVNohBWcThYYbdhtdkQdafuej770ioflkuvVLZMiJzqHCyE1eE3ORTXD2p7BWZwQ/J//x99m6BrqZk82Nv12bc1yuWW13XMynVBN59TdQFs3nMxmED2VUXz/szdczOdJpV5Ids2ed7ev+dmf+RbvPvuMvq354eef8/HHX+Pzzz5HhLQzDnbAxcDEJAh7RNANlnVjaRyUeUXdWZQpUFmOG2oGD8H2nE0n7FcbYGxgChhioJQaCSgi01zjneNhtUk0fglCKPJyhikmRFPQS0VRlChEotf7gPQOlKb1gZBlSdVrzB6SSjoIJY7NfKXUcQ0bY8hMhs7zRDo0yRhbSjX2PgBi0hj1FuEVeIVXArwjOIEXkeBj6v2MwMcwZuIyJtCiEip9Hv+nddJEOTRLhZKozGCyHJWXXzgA/Dg9j/9dCPHXgb9DIgp+h1Ru/NfArwoh/q3xe39t/JW/BvwnQojvAUvSZOb3OQTGKIwRaCMxynCgWKeyRSFHAyhkIEg5IunESJFONytpKQAkmrMLh1pUHN+0ww6RuAqRA3xERIEjkM9n/PzP/xJFecJvfPo9urtPuXAdq4cVn9285XrbkGcZL198i8vFjEmZMclLhlGkWQHv7u4wUhJsZDGfUWjBYjphNik4PTtFZJpCSvqu4WsfvcIgadqG0zpH+oq6bunqDVfPX7Jt9kSheHN/i5IgdY4i8Gw+4c16j8RzOZ8zeEsuJLVOnJBvffPrqBiTEE+I5DpHFxNOz8/Qecb6YUmhJL3wfOnFc+LQA47FpORyOqW3A9EHTH7Ou3fXmCzn7OKK++USGcEIRfCR+82WZlez2m1ou4HzeUUQ6SF6cX7Op29vGZzAdj0xwn634dtf+TJNvUXlOfu2w8e0ebhgabpI4yNZUTAXgrq35FnOqh2YlQVGCNrgsIPnYb3H2yQYJXVK0aUU7PYNMUZOJiWVMXgfaPue2bSk1AadV2T5hNzkTKcTQl6R5TlSalwY+STW4oVA9T1Ra7yUiSX7tGEaZZIXFBIl0ihaS40xxXEjlJlGZRplkgzhIfMgxjQc8BLhHDiJlRCDQMqAGh0SYxzHgpFUIjGWLCSdWClSIMmEShqnowB3JILR6CzDZDmi+MPJPIgx/hXgr/zIt38A/Mnf4dwO+PN/kOsLkcoWbTRGK7RKUvYJ36GPExcglSy4UVA2BZuD4rT3JiH1sKiQBGNUDOiQAkiIoy7T0863GAE1QhCj4stf/5hvfuVbdH3P7ZtrHt68ZhMHHnZbPrm+ZtdFvvTBc25vbviFD55xOZ8jleZuvWbftGR5hcoM1luuLk7Jsoy63rBtGvR0wqLMqbc7qsUcJZKM/rvVPUPfcTGbcn2/4qTQo/1kQrYqrbCVZzGfooVgkmU8Oz9nXQ+cTmZkRrO+u8GGyMN+i0Fy/eaasiooshKjcqQxFFWJd5622ZArjRGQF8m5rrWWDxfnEANSJTWuvutomxaVZUghaJqWaVnR00FMbNy6riHCvJoQRSQvcgbf0g6O73/6OQl8Dmezkgi4umer1ngk7bZmtd2T5zlt36FFQMuMTOVseks/0txP8oqH/ZLNbkdVVfQumYRpkyGkSOI/SpFl2fiQDUctXB8Cg3W0dqAYNGfzGSKr8NIgs5yimhBNhc4rpDTIEJPGqJTYGFBaI5RODzLyPYyGEmlMq4VECYlRGqOS2roxGcYYdJYhM4XK0thfPSlbpFMIL46m7VFGok/mUE8nf4fzDxNDlVp6qVFLev0MQSbTFMYTiVIQlErNdZ0lE7IvePxEI0yFEKlO1El8xmg1Cq2kFNMYMzaBRiAZIP2hQSUQInWSw2i1EOPYMw0RTVJsGsvfBK5JSrTJ5XxsMMUAqqz49rf/KC+vLtlvb7D7e+rdhk294/OHFW+3PYOLLJoObSK5lJRG0cbkt3E6myPzCUoZ3ty8RRnD/XpFFJEPnz2nms9ouh4tJL0d0kPbJVPur33wit/+4acUBr788gNe36542G0o8pJ9OzCZJPf5IjNU1YTXd3fsh5Zzecq7hwe8DTzc39E4yywrybKSi/ML9nVLNwzs+prBDVyentP1HZnWTGdTjJLUQ4eLHq01zdASXeLXnMznTCYTtrsdmVBsNhuuTs7ox/dt6PvURxKSk9mCbbtjU/cJxq01PkTK3GAEaGnoh57GDcxCwcN6SeuSrGSZ5wzOo6WgdgOL+YJmtyPLNDoY3MhcdT7ByDMtqfKMfdMhEhA0Cd+MD9j5YkZve4oiAcd660FqOuvJC7hYTHFFRblYoLOCINMIGpEa9QGLGOH6YgweSA2jlkjKNsTYtBTHUs0ImWgMypCN5Ys2JmUemRzXKhx8ZqWU4B4JngZNJOCjQmmdNsJD0CCMWKaI8ow2DgmLpInp4wBVGEtxLxVGpAFEpswXfj5/ooMHgFI66U4cex6JTYiSpIAqiEESXTz2KqSUKD1mEJFkZq09kYgPCqMCNqZ5OzFNaaSICBEStkOMY7MIQQnOX3zA1z78BrPZnNlMs7t7zfe/t+fdu2u+e7tmue85Wczp2o7ipCJTnomBzEuqyzNEPmE3BLqu5asvPkB4j287gohoIbj+9DNe390wL6dMZzNOigJPapLdrjZ8dnvH5dmck2pCfF6y+exT1rsdXeeoXY9Wgpfn59wNns5alMnYDT3OeZSWPH/2nHf390znC4qiwHvovGVwQ1IVy3IuT04RQnB+tqDIc24eHtj1A7a3fLq/psgN66Ymk5qz2YK27xARiqJi29SjmpZOuJB6j5KK0/kCZy0mz7ERqrzk5PQciWS33VAYxXqzZFKVIBW9T2NehMX6Hi0Vg7Ocn51Rr9fUdYsWOSEaXGi4223JjMF7aMeAJZRiMpmw3u55djZhuU9U+yzLaLueqszpe0vjPVleopUizw1KG5TOsESawbHZ1yxOq0SHUArpAyIqRDAIOYx9CkVUh1JXJBz5AWTImDnLg1hx2gTVmEkncWaJlhKtFIy9mQNTPIxavUqpFDSUQgWJVBIZDpOTBPhI9iBJPCkJd6cBgIxJg1eN61tGQRDpNaUAreQf2rTlH/ohBBid0j6t9Jh5SIT0yUJhbGsrkQAwYYTtphl2AoWJEAlKEpQipasxuZijkF4hhEcol2bm45w8zbxS/aql5tXzD3h++YwPPnzJ+dmMi9MJn7z5nP/p1/8eN8tN2oWC43uf/IBCdAxdTS4j1js27UC9rcnyKUWm2W/W1E1Da1vOTs74ze/+FpXRCO/IlGRaTLi+ueVh+8Dzyyt+67MfYoqCqpywDZ77en80NfIhLZAqywlS0QyOumkJIfCwXvLh5RW5llgPQUCQguVuiw0eGQKVSALNUookKyhSwOqtQ0aJQiMKDToFWC0URVVwen5B8/Y156dnhBhHicHUtG7rFilk8uVViq5tsD4QnUMJwWr9jqosCd6y3fdIGdk2DSezKfveYbTGRYuQktv1Dh8lvQ/JTnMYUMC+H7DWjw+fQKrI1bxk1VmW644iM8wXFenBStM35xxCC7xLHB81ZrJGa4qiJDcZ9RBxeUFVzFHTU0Je4WXSOOGAp5ASIdL4U6o0xZBCjju7ApGkIeWYTSDFsYGvZAKHqdF8yiiJ0Sm4oBJh8LDuoxjlN2PAR09AIUMKIGkAAAdUtRzjiJRJGSBBwgRaCIwQ6JDY4QGBJ+GYUkCTaP2HxG35h30IQAtQIqZoKZ9wAmQCiR3g62nXiQjUWObIEWkaCVERUUQbUaNIrvAuqUbJgywbj5xlKQ+YVfLqlIuL57x4ecHz51dMypLiGz/Hn/lz/xK//vYd13/zf8Z3A/fdLZFI37R07YB3gVwJYnR88tkb1nVHUeVUWbIvPJ2fYLKMjz/6CrZtWBqFw2FyRT6rqGyH7ZMgzrP5BC0NN7slt8slrbWpGavTA1kUJdLkPJss+GRfE2Pkg/MrnHdcnV2wbXrOzs6JMfLy2Qua/S5NL6xFK4VzkfWupneWd/crzucnnJ2csl6vsTFQmoyTxQmdHfj4mx/T9T0yK7B2NNEGVrstZ6dnOOcxRlHMpqy3W1AG6SNZlSfPECFph4HcKDwBbQwFsOt6boaBiVFkRpNlGbf3G5CGmYdh8Oz3DbNqym6zR2gDEYyKKBE5W0wJcUOXK9a7mgjsRkJ0piTOOZQczdIBZXKUTNoibQBvI+fFDFEsQGbYkBrrRhcEIVMmICHKCNoQpEzrRUnioVcWH2kOME4LD014eSinR4DYKNSstBoR1DL5sozliCY8mlUbj8ejvDo29g/nCUQCNIrEtZIxlWo6QibAxIgabVZdTIhpJVX6EJIvji/9SQ8e481PUN6kTem9P3IElFSpLyFSpI0iNa7MmBJKEXEEYtDJniGCdamm1CohU9OoN+WZcaw746FpqgtmLz/m+auv8urDl1STPCH3soqrV9/mn/qzf4nr9Z5Pv/N/E7uUQvZ9z/16TV3vOT8/4+vnGc9mZ3zn+59ws9mhZEbTN8TQ0NzdsphNeb444Xy6IEhBoRUvn18xyRVFpti2DaVMGJWr+Sk5GTHeUGUV2/0Op9M552XFttnTuQEQWB8oy5Lzkwv2zTXtvmY2qXjz9nNO5jOGYJlMJxipWTUN19s17dCTScOimvH29pY2eLq25ezZIhltLxa8vbulyDLyScXq5oZt20GI2BBZ7/bUXcN0PsfHyG5fo0jTLu8FNgh6F6iKLD00OimiC6DetbggqIOlGSwvzk9QWtO6gPWS6/WeeWGS8VVv2bbJAHs+Kdi3HZ+8W/LyZEY81fQ2MAyOQUaMSKP7PNMUmUlMbesIokN6yXRS0XSBi1fPGKTGaU1hKshnkE8JMlk9+AhIjZB+zE4VHAlu4hggHkn4j5Q0OYLApBonK5KELtXqOMoVKjVOD+TNiCKMYkcehQuPz4AQ/tgPAdLYNso0DDgCxVLmoUiNVBFBH6HqTxqqP60NU0hdaK3UMYggIsKnWfWRBCdSFxmV5viZlpjDrD2kujTKZOBk1Dg+G7/ukrb/E4ZhPAaS6uIVkxff4Bvf/CqXp2doJbAhsBkcnTH80p/4Rb50PuE//dX/kP/xv/kb2Nqxb1pev3vLz371JRdXF+QCptMFxWTC917fcLuvudsKNrsNQ9dSIAinJ4jRgvF+u+XV5RUffPObOGv5/vU1P3h9zUlp+OrVc97e3DAvclbNHpMbep9KtXq3QWhFZ3smxZSudxhT8He/+wlZntMOPUYJLs9PmRU51mYoKamHAVUUnJspy+2a0uR8fv0WbTK0MszmSRXt7bt3CB85PT8jAjc317R2ILrk1i6EoG4aJvMpXTfgQqQqKvpmx+A9VZ7TtiGZaAlB31t2jaOShrLIUMqxb2rMJE9SiFIRpEbJQNP3yeBbKG7WK5x19G3CdcwqQ1FkRAF3dU/nBj56vkCGBM82WvF6uUZIi5E5u7pDKE2VF+SZRpuSLD9j5SW5LtDFDKezVOZKmcb/QoxC3OrYIEWoI55CjD0Lgniilx1RUSADRziAlBGkR6iA1HEMICkLkSpl1EGk3oqMiqgcQSfofCp30oeXBxJoeh2hxAhsTKhoQdK4UaSG7Tg4hiiJIvVqlEk0ACX/EODp/38cQiSznsxIMp29MgKCAAAgAElEQVQisxQysVnHNFAAcWRExhhREoxKvxdDIr8JAlJEtAQlAmqk7DOOdYXkuGsImbIYkeVMn3+DxYsv8dHzlxQj0GY7BDadY5IbvnJ2xc9d/RIfzCv6tuZv/Y3/hd467tYb7pYrrp63TIuC4DoWZcn5xICcstnVvGsbXn3wispofAjoosAjuV2teHl5RdO2NE3DxekZTd1yNqlY1w3LumZuJuQ6p3M9p4szXn+6ZN93DCJBk711IDW73Y4Yk6OdUYrBO9quw9mkqhVCoA8enQu2uy3rzYoQPF/58COyLKdpW0SEbVOz2dU8v7giKyruVw+sdnsyk+Gd5/T0hPvlMimsB8G+6SgnE9a7PZMip9A5bQhsdxsylbgedWdZ1QPVfIIuK9x2y3SSYa1L+Kco8R7yLMMHh4iCLMvYt3uUkEzKAuMj+7ZHichHL045mcz53/7eD7juUsYTJDT9AFGhCQjR0juPUP8vd28SK1mW3vf9znDHGN+YLzMrsyprZHVXFckWWxwk2JJl2ZZgSPbCXtreWPDC8NZaGPDGC28NGDCghWFp4WkpgYJhiaBMmDLJ7iZ7YHVXdY2ZWZkv8w3xYrzzOceLc25EZLEpsrtho8BbFciI+27ciLj3nO983//7f/9P0TYtWexZlsODQ9p4Si0SnNO0MqIRmgYVCioFSBDKYbvQGiH4+14SIixi+2M3eLNS7ijqUgaAVKrA/VDEuvc8/CJoLXROIJ30bReMIJIKIxWd9EZG9pX6DrYq//hudEp4TpGWfnLrPgPkggKZEggFSvpwLvqL6nmI4B1EUnqPQSkPfPWGIxgP60INnPC9QLzr5mtYfCs//xDO+kcvSOuCl4ELOIqnpAss+WhEfnSfg6Pb5CqhalsKJ5kVHQjJySBilApkkvHe197jv/hP/3Niofjxt7/FzWLBoydPuXV6RnZ6gulaBjri1sGA6VQRRQodC1bzJakaIazl+uIZrTFESvDwySNWxZp7t++Q64h7J6fU6zVPFnNODg+IrGRRrYi0RAvHwXiIEyPmZc2qrNg0FUeHR1RlyXq9RmpF1zZYDLeOjlBKUWwKhNTY1tPSy02FUoo7h8ekSjNfr6nqirPjY1abNTpKuby+oeoMN/MZWmra1lA1NSPnODg4YLVesyk9Jd5VDRaBkIo4SrhcrqkbixVeYnBZVCjhmA4SX97eOYZZwqZas6oKjlqfvq6qgvv377Gpr1FKMx2OeHp57UNaLJuq5XCSQ2sxtuTrr5zx4ZMZsU44v7zG4VO4xgnvISlF0/oWEHXXMpGKPNashKUyhrKuEa1hYAWJEygnfUiMoLNdGGt9/dR+DdVu3O64F6G0XvSFaiGckJ7/oaXwDy09KTEYJYmmw2CsINIS53QolFNB7Nk3l/Khi+8z5FwwGEoQI4ikIEKinfQtKa2v87VhnKtwbKR+dtTjq208gEj5R6x9vIjzYOaWIOZCsZvbFccJ4wVShHVo6zkArfFq07LrwHShyU5fjctWgxIERJrR9DaHZw+YHp7ydL1heLXAxiOklpwME0ZJjBKesJUNBnzzl34F8R/9Z/yv6YirH3yLh+eXnB0/ZBorBuMRTbEhG4+QxnI2jNmMJzyTmucXlxzZjGGekOc5Kkqom9b3P6kaTkYTqrJhXZXcOz5gud5wOZsxmQ44TId8dnlF23YcTqasm47hcEhUtWzKguViwTDLsUDRduSDnE1tWCx8LQzA7VtnbKqKRVExHiTMlkvakKLO8gHLdUHVdCzmnrQli5qibvwKKhSdE8yWK38/8NwGZx1N01DUJScnh6SDEc9ulhRlR6QUiNanIK1gtqwYDSKGaYJWmjSJcUKi45Sq6cDBzbIgjSKqxmCMV2QvmxYlpFcda32DrQ8eXfPK6RE4WBcbVCyJhAo4l0bgSJIEqEmSmCjy3kSMIZNQxwkmGVCrhMJJYrtz/Z3tsEJh8LUsXgXWZ178w3MuejEqsL7IVb3I+5BbPQ9PS9dKB+DWeynWCoRyOOPBVe0c1jUoCyqyaOMwVgRyGttiN4RDaONTs1b690pN7DTKeAqbQWC1x168ByTQ8l9ZIfKv3L7axkN48DPSmkiG4qGeBhz6cto+DWVNqGr0zXBwXhjGdg3WtjjT4Trf88IZH6cb29H37hPCbTU8hge3Obn1Gmd375Mfn/G7F4+Yd5fcuyV4cDrhIFVE0q8qDodSksFwyJtvfp1/7d/69/gnlxfM55d8/PljpvmQV9MM6wom4wGJUhxNp6hkTHo14/L6msvFAmOHnA2nlE2HMaCjlKpquKiv+OzZMyZxjO06jqdjUoEvXgspOx0lfHz+mOlwgjWWzXpJo+KgAOaVrpq2xa43dJ1hMplsV8zlas1itURpjXWCsmoYjCWdsbRNRRrF1HXL6ekJR0fHdKZjfDCmqSp/Hbucm/kNzjlGgwF11/mWkGVNNsiJsgE//OADhoMJUvk6i7KqQFqiKOJmsaLrGo5GGU3TsKxqTk7P+Oz8gqYzIATzxZo7Zyd88fyCg0HK8XjI8+UK5RRSNayKlk3TYI3hw8f+fUIp3rpzm/PFnLjuSKOEovFFazLSjAdeMrIyEdJKOiUxKmcZ5aQyYeAUNYKE4MUKr0BnA9HK9byM8HzrfAg8YUt4mUgJIVz2oYKS/nUUVn2tRFCUDyUSwoc8TnsPwyGxLiyiWqKVpOvYkyb0lAXhfGiiEYEAJnznP+c9ECHx3KFguCIlvOchxZ8y+/7s7attPGDH0lM+d+679gVkOwR+FusRZ2NxdB54sjYYjBbXNmA6TOsftjNY46V4+j6jUnlAS8QZhy99jbv33uZgMmGTZvyRnPDk2TX/wShjqCckcuuwhO8piGXE6HDMe+/9Ih8++dt89s//CV9c3TB4+JDpZEKcRmSDhCQfY6xjkiccDnLuHhzz/ic/xllIhgWrdUHddQzyjAJfzLXpWoR0ZD1GESecHR7x/sefUNUtzggOR1MGOiJPJKv1mlE2Jk4SlsWG66srkiQhSb2a2eXlJUeHh8RJQlPXNE1Dkqas1ksGeQ5So6WgqgtErGjqjsurc+bzBWVZUrYFk/GYcl2QJZGvLzId19fX1E1HNhxx/5UHDMcDPnv0mNnNgsFggjEGKxVdKJc3TYfE8NaDuxTFhstlyXh6zOxmSd0YnBUYKWiModiUWCRCarAlw0QyiDOstESR5GK55P7RhB89vkBJwfWqpGlrXrp1yuXFNcb6Mn2DT213TtAYyaKCvIM8H1LGGaWIiIT0wKftsGiPsQkR9DIEVopAqhABqN+FLoKQIQyApRK+j00kxTas8AZEBAMSjIza6Zq2hN+uQu9bsTM6veEJkh690wGBVa0DvyORkkQKog40HuPzkZHAhdBei7/IYYsIFzkATT4960vo+0oCYT3nXDiHNR3OmgB8G78yhua+pqmxbUPbtXRtizXeU3HCIbW/4E4akqO7HL/0HieHpzSm5VHdsEmGfLhc8mw5QzUnWBsh5Y7W6/DZu0GecvvoiF/+9X+bxWzN/Fu/yefPrrg7/YL7L5+xXq9RcYoz0LYtmBLhOo6mB8g44dEX51RNAEqPj7hzcspstUIaS6Q0r9y9zWw2wxjD85sb0iTDtVcgJMM0QQBF1RDpCKU1i/Waoq2pTIc0mm5d0EYd49GEsvQFaW3beRFp60iy3KueFRviKCaOE5abkpv1CqkV67qgqkum4wmzyxlRFFGFNgxV43DWt6MYjobUbUW76Li6ukIqTbEuyNIUayytMeRJimlrjg4PuZ6tmN3MyUcTrq9n1HVLnmdEaUTsJEmS0HUdVVXTjYfECpI0w6FJSsW9gwnn8yVZmjDIIqTUbKqWuvHl+0k6YLZZIZ1gmGSetGYdXZwjJyeI7JAim1DFCVY6OmF9Javy6Vj6qed6+nkYn1L7aye8UZPSG0O1BUp9mrYX5dFCo4UikhotQUqLFBYttQ9phOcmSaVwxmdVrIROerA/1oJGC7qur8AN4096kE9Zb6AiPFFMO+99BD6qT8/iv4/CG62fw3Z8tY0HiBdStUiJlB789MIpXjzFWYftU4bGhlZ/voO4bRpMXeOaFtM0dE3j8/zWeo9F9f1egCQjv/sOk9tvMRwKPt2seC4myDjm5PCEy+UjrhYz8knCUCrfEIqQ05fC1y8kCTrLuTx9g3Z0h5vrj/njhx+TJIpEJwgVEacZUZwQSUGWaQZZgtApVzc3XM5voDMMywGtsXSB2NW2NZerJeu6ZBAn5GmKFL4JdNN1VHXFeDjm+saDmqvrK5TStE2DQLApC/Ik83KCacLmpkAFMlaWZaxWKwajIU1dbdOCm6KkrGt0HFG3DWVZgoPNekMcJ1hj0EpTlhVt2zLIU25ND4hCufvjJ0+9oXaO5WIBDq+AFsc4HPnAG6ur2ZKiLFHrCoGjsy6kLh1RkvgO8UL5grui4uQoI9KSy0VBZxyPrxZkecRNUXF6NGa9qZkOc2Zlw2K94WASh/46MTiD1ZokHRAd3OIqO2QVD7EiwklNpKKtfJ/AA53I4GqGBaxnjEqh0FKFmhGfdZFSBNq3QKug1xE8CiWFz7SE8EOrcPwWQPXgJ8IRSYlREucUrfHAateTzqTwrFJCf9vgCSkJygVux/YRJBG3x/epXE/AlPtW6KfcvtLGQwi2lF5PBQ45c7sjyPSirtZar0/aGWwoDrKt76dq6oauqb3GZ2swjfEVhgrAp9KsdJAdMnrplxjdus/cXCPXDWZ5ydHpbX7xaIpdbvj4asbR0RGZjrfishBujIBNU/Ho2TmfrhuGR2/Bas6Tq0vy6AtUmnIWKfLOkuYwznLunh6xWBZIpXhwekYsNR89/ByE4vJmTrnZUNcdWgquTE0sIJYKYzpirRFCUFYVySBjtl5zMbuhaR3j8di3T5SKNElwwGQ0BuBqds0rD17BdAZhoa4qlNYMhwPUeMRyMQMhKKoKoRV5OiRzlrpuPIXfEeQQJFVVeQFg4WuOqqriej6n6Qyt7cVtDEoITNtti8KEhuubGw9EhgDeWUeeRJRF5UvhBWzqhskgZ1MURDpivd7whS14+fYRN0vfo3bedtwbZBR1Q9t4UaDxcMid2wM+/PwLplmKEpb5umE8HHA4nZAOhmxGE0qX0MoYLSOU1CRCbtOrvaHwfUVD7GDCv70RUaHBNiGLofZDDBG8EIfSnpQYeSZ64BtJIqnQIiyQIeNrA6s6ClXksdYYo+mEr0VRQdcmTABvGKQLIX4oywdPQxdBAxi3k+IUbsvc/gtrPIBek2fbF7bPqu9jDtZaOmMwncW2HQ6BsK1Xua5ruqamqztPj24Nzjovfiy9O+oC0pVOTzl76XXyyZSrVU0erXizWjFpp0zinGZ4wqPFF7y72mBGue9MHmjJxgnKpuH84gLdbsjuPeDz8RlqMCD//v/Jk4sZSfQJbdNwcnqL6aEgHY5Q1jIZZswWBVfLNVc3N5jO8IP33+f49JhJnlPXFW1rMK7j1mTErGtxrqMpGm8gtERpSV3WKKFQWKrVhvFohHEGnC/Q6tqWqvEiO+fnz4iThLPjE7RWpFmGcZZnz30R3HK9Jp+MSLOUYrni4uKKQZrhnKXYlDTNhtFoRFnXSOE9xKY1zDc1DoiShHpdBP1YixEWE8h8MtJcXV0icf77Si/1OEwjLII8z7FOcjjKqaoZJwcHfP5oiYwUm6JkEOeAxAhFhCPREVVRMxplrNYrKtMy21TcU5Kj0Yir+Yx3Xn+V733ymAJBazUZOctG4wY5Vmpa6fk+Ybb7EgXpx4aTvuu991D9DHeIwE4XWwZpz/bwmEef0ZDhmF7ta8/TECo8F55/JPuFLIQsDjrJlgmtpAyavaECDk9ToK/klQJhg/chvKyDwhGFb+zBXtercYb3/AUlidETuIJ75YTYWkqxZ0G854Hvrm49lVhZoDV0XeihaoJhMaFjuGTXsMc5hJUko2PGk0OqRNG0Y2S54htpx/X6CW4yJkpiLlcRV+sVt7pj4sh/B+egMY6nl9esq5Zbx6f82mREuyi4d/o3iRKYf+cf8/j5DCEETVMjdUQ6HvHS2R2c1Lz/2e9zfjkjjVLuHh+R5i9hjOG1e7fp6obz2ZxNXeGEZLZa8ubtM561C4Z5zGtnJ1yvS85vFuRphnM1GEvbNDSNp6tb66id7+5Wdy1NFNO0DessZ7lcYJ2jqErKqqRtW05PbwHwow9+xGE+RDkJnaVpGmSk0UrQWIMIlZlxFLHarBkNJ8GYW9qu85NFR9R1g44iatNSrmuE9GXqpjPUbcUwk0yPRsyuVhwMR8xWJRzmjMcpm2qNjiLKpvaZCGPYbGrKomI4HZAhieKIZ1dzoiiFpmGcpdStz8LMNw0/+PgzDqeHrG2ESAa0OqeNMs+rkJ74tRUNll6w2AUD0qe1kQE5ECqwYH39qwxVqmqbVelTs97z6EFM2adrhWeQyoBzyACq9h+jlERbn21RYkdp77VmArF0T3vGGwLbq4uJII4cCGPK7UiRvZ8hgmTCz1Pd8tU2HvQXKPzknpMRLL9PVfXhS5AnDM13vDXxM3vbaUsKMG7vfB5Icsbn5kU6olQp89aAThjGKeOuoCnmLJczBse36bIhX6w3vFJVXhFKQmMsz65uuJyvGEwOUVbyb6B4bTLgppiw0H+Ly/mMm49+B3l5hXEdjfPKZyenZwzzlG++9Sb2FxSbuqGoK9Zlxc1ijcUxGWfkiaasWy7mS0aDATflmjSLee+NV7m6WfHo8ilXixXjfESSRggD1li01sSR55BcXFxQVL4hd2sNR9NDitq/Nm1LWdfUbcd4PKE1lmq1ZpAPiOKYJEqx1rJarZBZTFn66lmtJHmWU7cNIpD4jDG0bYuxUBvfeLrpOrLce2t1UdBai2sbTNuRRhGv37uNEI7kRHE1W5NmmrJucEJyNbvBWijKMmQM/IC/czymrFteOpmyLApW6wqdQNcahrliuapQOmI6HCO0pKx98ybh5YoxYf0lpOg9sbVfnHbjTvTpWXxI4SRb/Zie/NX3FRIhVNHShylasBUFUn0NjNjC/dvX/ZDc9R0KJEjZk8x2ueAvF99tW0Z+ibLR63wIsd8YLYx7tz3gp56T/faVNh4CQrmzB536ltNSCp+uZYd77L/HByP+hvc6ks5atNPIwPfo2aT+Pf5Yg2ZhLGUnGGvNrekpV8+uGGO4unlEPjlikox5srpkvlwxyAfEKuJ6ueLZ5YwoHxIPxpxoRaxqDlaKPzSGzeSAxcvvUH3wB7Bao8SKTdlQtZZBPkCmKS+dnRKnGbOV71NrnWBVtVRlgaRDA23rsYU0jjkdDUliiTWK7zz/DNMZhtkQLQWngwk3yzVO+tg4zVKWqyVlWTIajdg0FYcnR4yyAV+cPyWKYrI8o7UOpEJHCW3XsVmvfBFd01As1kwmE7LBgEWxput8H5UkzSnbmqqqgkp7jRCCoiyxQiGkpmkb4jjGWuuBUe2LzTrnODk65NU7Rzx6ck5VlwzGA1SakuUJxbpgvSno2g7TeSDRt9/wquhZHNF0jufXc4aZ5vRgysOrOVkUkWcZZe1I8iGJ9HICZefo+mI2HQWaeVACE9Jrc/SM0X4w7Q0shzcagYyxK2+AbXzdF8RJsXsIAni5nfQvdoiVfZpX7H+oe2Fei2A03N5i+JMmTFgOXzBI283t5hSCrQL7z7p9tY2Hg8h5EVf/g31DJ0IYY8LFNIFejhRYJdHOIp1PtUnpy/mdtChCuld0LwCuQnjeQXX5mM3yhmQ05iCS5GrAKsoQ6yumeYrpVuT5EZet4mp+w/H0gLWreXp1jYg0STZmmETcGibgNK5r+JZr+edfPOZ5m5KfvIF4+kPiTUtjDeXjp5ycnHP3/j1UlGKNQKGoqgahJONRynCU0LaGqOto3TOOzQCs5fbRMUjLtz/4hPPZDGM7mrpmcDCl3GxYrzckSeLrJrRiU1fcun2GFIJUDjk4Pub5o8c4a5mMDnj87AnGGExnfCWs9eXexsLVbM44SzGuY1mWdM4RJwla+FL3xXLpDclggLO+w1nVtMTam/dIaRCOqm3QsY/AEZKj4yOSJObR5Q0dgunhEZ2wXF3ccKQOWKwKmroh1prxMKWua4yzyCRibbwkYqY1Gng2W+OE16pIdAQiYjzMkUlGPh6z3BQIaRkmQ5oko5YKpKXDbUvaldBbNqgUfTN0t/VQ+8XLWj9B5dZrCLG1cF7TA6BH50SfrPFERiGtP5Pc6y+0TekGajsEHIOdIQueUW9bxJ4h2r3298yfwwTv3Kelhe3L44KRC5/7s/sdX3Hj0W+9l7ATKA6rgNtvz+c3vzB45WhP8fVglzE9gy/c7N46A74ruaV7/gHF+fu8+tI9zrTGKMXg+D7r5Yz7SvK8XCEHR0TJEZ/Mrxlf3rBqCqRKGE8PQAkO8pg8ElinkK7mZvaMh01He+8tqnyI/J0KOfuAU+moupLvffARyXjKyXGKQDDOciKlqW2LUIp8NEJKxfWzp0yGIyIVUa4LHJKqaqG13D06wtkOhODh5Q2romI4GNC0rW/EbTqsMaRpSpZllMZzXcq6Znp4QDYeUT9qkFJydHzg1aiEL0Sray8f2NmOddFRNQ3G+R60VgJmV8thrZcBWG82OLwKeO/1OeEYjUcAVFW9/S4Xz59jmxpjWq4WS27ffYm2hfViQ13W6EjjJ6qkajqcdsRSslgWjEcDBolmvlixrlriyLfpQPowaTrx2hxOKowQyF4CQKkXV1wBQli0ACFcYIb2FbIBxLQ7nf0tRaBnhodUrZQ7rka/vdCZ3luHLYa37374IGZ/jPahkNx6N2JvP+wMSP9pW92QkL3q9UVeeM8Lx8r9r/BTb19t4/GleNDv2v+5bi9s27/YDokHu5SSGOOp7VI5LywrQol1+IzQwAVbbFj8+P8mfffXSce36GyHzoaI6SmynZM0a7q2Jh1O+e7Dc6rVh7xy+4TDW0cQJRykkmHiB17bCWabFQddzdnJGZ/qjDZNef7mX0Z/+4KoumYU13z8xWfEg5S/8iu/6lcqreicIYtTdBJjjaEsSqrKN21WSng5Qiv54vKaFi+CFOmI6WDEs6sVB8fHXG82WKtxzjGfLxiNRrRt68OGNMa2HdZZTk5PuVpuMDjee+9dAD58/0doJTmYHlCWJUUc4aTEGuM9iTgmjjSm7bYrb57nWyPSti3G2O3E0lqjk8indY1B64jj42MuLi5ompZiVYYshyOJFFoJirJCSEmapmgpWBYFdWc5zLNtBq5rLA+vZ1hn6CzEGqJIg5JMDqaMxmMcEZ2DoTHMi8r37emLKgN2InDEDjIHMZ5gJQgJjT8RJuw4Rn1oIeVO0yOMxH50bg1PH5HsL3phVzit273a7tx/LbaHvTgH+s/deSC9XoeU0jcv2zM2MnDkRd8p7ucIW34eIaH/XzYhHA4vE+hl7f3+rWiKDftscDExSNEz93wqSsug1iRAsOv74pz3SnqgFQvlkx9zffnF1jU1COLRARsnyDqfvahRfGvV8MnTp6j4EBUlHCSCw8zn6hvT8Xx2yaaoeeX4lF8/PfCue5rQ3f8F5scPeMqARQtVWfL+hx/y0ccfUawXWNOSDQc44ZXjYx2hlGQ8nVI2hq7xdOx1tSRSgvfeeJV3XnuV6eSIRxc3xGnE4cGE48mULE9YLudEQjAdjtBaYk2HqRuEEJwcn/L0yXO6sua1lx+wXiyZP7+iqSqarkPFEePpBBXHbKqGm9UGpYPmplBUbYfB98Ip6wYZxdSdF0EQQqKjCCc9X6Qpa4QVjPIRMoQ7m/UK09Y+fWgsCn9eqTRS+2ZXkXQ0XUuaxkxHGYMs42K+oWp9fxud+LYIpjMY67vcv/bgAXfvvsRgOEIoSWsMVdP4viZSg/X0btGr5gvlOQ/4kE3ZPbcikBA9Xd1t+wZ549HjZn0rUulD4BBeyz0MBMLE7/8TPpXqq7zddg5vOSMi6HuEVqlb4yADrhGIryJ8NiENLKzbpmG35LXQ6lIEjZKtWDiCXjPvZ9m+2p4HsAOX/M3qn/b9W5yze1mYXvw1dOYUnjCDUj6WlxYZQCMlgmtqBcb6XJiyDrm+4eLhD3j95XdIBjFKC1Q+ZH0Jw7JkfnPJ+xH8aHbD28OYsnNk2nGQRiQC2s5xObvhYrYgTodMs5hvbjreb+AHa4M5PGP53r9J4sBefMQxjnJR8Pvf+y55lvPy/Yh8MCAdDj2eY71WZxTlII4xncE1FWfxCcPhGNl15JEC2fHy3SMWyw3nywVCR+g4wjhLojXDPGFTew5GXTfgHHEcYdqGzeoGISXLTcHhaOrrXYzPmqSDgW9hoDWT6ZSiKKiqGiEapFI0besJfEKwWC5pmgYVRIjjOGY+n2Od7xOTp8kWpFuv134CCtCR9tkyaxgMhhjra5XiyBtO27Te0DtJ2TrqFkxX0zY1TkCWDmhrPzmVUpzdusVoNGK93hDpCFN6jwfUduw426/8wY1xO7C9DyLc3rjqQxX/frf9V4R6lz5n6jkfwTsJ/wkpt+cJOdYXxmzwUfYIWz613nsuL/jaDrYr6N7E7+3LC+GOk4HUFzx4txcq7X7MTzsht9tX3ngIKbaqYfuXqqel7+3a3lTpergqoFVWbvUat6CR9YLHKlxo4TzzPxYp148fM1vNuTc+A+mIsgFmPCVbzfnsyWd8m4I6OeB3l9f8erHkl9QRWoHBstiUfPHsOU7n5PkYheSOWfF3MseT2HCZHmDeeI9lNUM1G/S8Y6ITvrhe8Lvf+SOcgFe0ZHJ47LGGrsW4xrvwSYTOBnS1xhpH0zmKuiJKFUejlKPRmMvhiiiL+OLZBRkdr905RUpJ5zqW66WnexclTdvS1/asyzVaa6bTKfPrOU3dEMmUYlNsL6+1nj3aGwet9dadHwwGvmCuLEmSBGs9H6RpGrquI45jWmNYrtfEUUSWZVjn0FphgwwNHscAACAASURBVAqZtRYd6dDQK7RwFoI4jmhXBadHh7QdPL+4YJjnqAjqriXWQeYvqKCfnpyw2XgCW5zE1J3tHYjt7/hykqGX6BOuD1V2WIV1zhuz0L7D9kbkT8xot8Ul+vGI24Uw7BmGMILZ+SV7KVzntraoH88vTojeg6E/aBvVfDmFK/qQXBDC9N3f/U/YdZH7WbavtvEQbPVExZ617q9gT0vHhcaRzj+ECC0VhC+N9o2goL/B3qXzGRmJJwUpGYFO0Nkp1c2GR08/4e6tY1Ts/yYGBzx5/pz2/CH1KMK98jZXi5gnN88RzR1MF1PWFeeXlxiVEGcj0BrhYBrHvKpL/v3jCf/z2rBxQ8yb3+C4WXD2JCGVHeX8kg8efU7XNazLgjffeovJdEoUaZzxZf9SgjSOJM9YrlYgDWg4HI95cOs2zy4vwRpO84xylHHv+BWsgMvLC5rGso5jrBUkwwHFZkPbNcRxQtta3xcniijqkiRNQQrW6+V2ABvjyXaR9qrhXeep5l3XBYxjp6sphaRpGoSQDIdDAJq29UakbRlFmrqqcYiglhVS0FlCWW3QsRfoTaOI6WTM1WLDelOwWq6IIs10MmK+XCAE5FmOEopOtgxHOadntxiPxqw3BXGShdDU99/pJ7IfCn1Y4vEC6V6cWP2q3Gc/tlk9vKK5DZ3rXchK9Uzl/SHKFouw4aUMoYbfrPCZnj6F23safXDTp1RfPKXHMkxvsPYsnn+/3P2GLSj7osHb+S0/T67lq248wHsO7BSjtwrq+3bUBSWwYO6t6bDOoJy/acoFECzID8qQTRDIgEwrpNBIlSKs4lQZ5MUTmrJkmIww1tDpCR/MVjTLa+KTd4kGCb9x9CrN+jOez69RSnA1n7Mua+LRETpJMc6vVpEwHE8GfFNbbqTkN+ct794942vDv479I0N7/Yy67djwmPc//ZzOWlQc8wtvv81BdkCsFM4Z0jTCVBVVWZFnKVLAeJD5akkpmTRjDoqa9WrJ6eGUSMH1ckESa8bDnLWxLNclVmhK05InMVXZIKxDOXh+/ozOGKQKotMI2tqzOo8OD5kvFi+g99Z6TY6+xiVN0+1tG2UjoihCKcVyufR1Rz3WZD2oKqWiNi3OQp4lpFmG0mrrbeooJRaSo0HG+cw3C7fWMl+tcPjGUaPBgJvFmiSNeO2Vl5mORsRJSpJp6rrFa3cC9AzMMKzYee5brXzRy/nsKYE5ixMSiwsYRFi08F6bP7N3FfaDFe9N9BO0f+wFRT2mEb5PbzK2W3+dt4DobtuSHhHsBIj23hpCLhviMCG9Itr+u3bf+883DX/S9pU3Hi+maLcB2y7V9IKrJhGiCzfVX9RekFY43whHSZC+CwbKSYyTOCNBaRA5k8GAO9MDyvmMm9kV49GQ5x18d1UhdIpMUgbdhtdjyW9MJxhxm+9+9piLq0uESpgcnBInGUhJaw02rNbjSINq+BuyRYiYExWTjx6wXr3DuiowNwtENmZVrPnjzx7SSUBHvPna64zHA6TEU+2D/qiUvlS9KAqsMXTGooOk3t1XXuL85oY8TjmYDJBCsiorhITPzDm1FUjj23Vu2o5ER5SbguVmA4FuHkURSZJgQquK1XqNMYbBYBCutdhmT+I4Zjwe45wjy3IWizlFUQTV8thLR4bjT09PWS1XrFbLbVgijOPs6JgWw+efP0IrTZbmLJZrzGbFraMJ69qyWq/Qoe9smqTkSQy2I0sVWZ4wSFPSJEXHMZ0TCGm2U7n/ztv0Zs/zCRhZcECCl7vLI3jgfB8kDfv3cROxFbak94p3wGg/YvdDlRe/z5/62JM57FmuPa7Rf5RwYod3hDNb37CZ3Se/GPLvnrk/YZh+mu0rbTw8sLmTbRNBt9F3z7IhqxIAIsA5E9y9vvAnuKbWryBeyzSEM4SQxTfoA+FByYPxMY0e8PzmmvjJY6a37vL/rBu++/SKb0SH3L/1NmNZcbu9JhdTNoMpv/m7/xdfUzXf+Eu/wTQb+U5iHqb3N1zHCASjXPC6crxxGPF7Nw1Vq5APvs76yedkF9ccHd1GS8HNxRN+9PFnaBWjhOL11x4wGGTEsS/n1zrahnJKSqIownQdTVNzPBlzPB3RdC3WOrJsirWW6WTA2w/u895bD/j2j37MJ48vKIoKKTxwap0lTVOvPBY8hLKqtrVBSKjrmjhJMJ1vyqS1pig2aK0ZDAbMZrNgQDJvPJyvqM2yDKUUSZqy2axZr1fbiWg6w9nREXmaUtmWWMdUVcWsuUErybKzJJs11jYhTEmJtCZPIqTrmI5H4BxFW/Pk/BwrI05vne2BnC+Ciy9EvmFlttY3A9tZmX7Y7E00t5dpsf5hAv5h98/Zhzl7J9unr+8f14cmO4p7z2cKhXZW7IU/e7jsCyjOlyZMME99B7n9w/qf04dhf8pZ/tzbV9p4gE//9xdtK+Ak8c2KpPFotwThPBEJJ9HW+XoCDGYrM7jNbnmjEe6j3F5hwXQ8Ik9TSltzbxBxWC748HzG+5sNZVPybHTMYdTwa5ljuXjKcnzCZ43lB2XEzdVj3nhHUJmgWG1ahPEZA0JtwSSNORj55s2rLuf78wo9PGD85i/jFgu0hihJUShunj/ljz/8FKU0Drh75zZ3zk7RccSyWJHGGh1WdofBth1ZLMmSFNN1HI7HPL++wpqOycGEREXUbYsE7p/dYpAPeXp1w828ZlUVrJuC6cGUxXKF1pq2a0FKTOhYhvWam77QzmK6BoFPJ/fGQmtNXfuOtXmoY+l5Hl3Xsl4tghfiMZzDw0OwhjxLuJzPOD49QW82ZGkaOAqOPJJ0nfU1MHGElpY0UmghmOQpoqsp2o7L2YpiU5DlA3QUMRgfbus3XChfdwEI7cMOPzo8QGtF6ArX42jW0RF4mm6XbTEmgPV4LM0hMWFsOWtBvbjObxd2t/v8reEIAssyCA71nspWEkD0VbTey94ZHC925U+755X0n9P7N+H4HQAstjCPC2HTnun7qbevtPHw4NCOcRcCQ5+Gkmw7XwGhdUIoeRZeVVzR4QheiNt79DdK9gCWIklGZNkQKR3HqWaaZayuv+CanDadwPiEy9EB+ZGCzRNuCcsHj3/MH1QpF4Nb3LiYf3l+yfHpGbFWaAxxpJFS0+FIleA0S8g0SDoe5JbzSvOssIzuvEb56iV1uWAoIdUPEFHE9dNHfO+DjzFW8I13v0asBOPp2BPHynZb9p0kMQKHMHarESHqmsPhABvSorWKyNIUIR0vHU5IIkXTNlxdrxgNB5y6jtlqg5COqi7I0gwlNet67eUdhS/5TkMrhFQmWGuI4iQoe3dbQ5KmKeu1r38ZDAYYY1itFtv7OhqNmEwmFEVBWddsNoXPzARQtmtarLMkUYyrBYM8Icsy4liQSIfUQY5PetyqLFoWqxqw3MyuiLMcGaWA9tXUWw/EbcFSt8fX8ER054vewnfscQ9re3GpsD8Yny3usA2FemB17xx7KOWWVObfFf7/UnYE4b1VelMSnu0V3+3wmF3G1+1/liD0Xe2TDDuQeN+Q0XvlP4fr8ZU2HhDwjm3cFwyKUr7BjfQS+kpKb22lRFlf1dhXMTohtvoFogdOey8lnE9IhdYpWkWMBzmjwYhNVbC8viarLIdv/VWeDceoFE6nt5FRh1pecP3Jd3lmT7H336G6dY9/+uyH3H/0Be92J5wejXyrCHwLwMMkJo38apMlGUOz4rWR46p2dHHM5PV3qZfPsR+9T20dm87RCE3dlHzvo09YbpZsqiVvvfYqh5Ox7+EbRYiQFsUF+bqQ6sziCJumtM5St43HCoBhnLDaFBRlwfFkxF/9xpTLmxVPnyuazlfhlpWnt8c6IYk8V8M4C1pj24448rUq49EYlGa92fhao86rnZdFAUKQJonXLbV2C6Z2bYsAiqKgriqstbTOkWY5AoU1NVJJTGvAmQC6OlCSQRYzTiPKriMW2hO7JDjjQ7T5ukZdXeNUTNsJJtPDPzGetpMf6Fdiz0MJBoQXw5Ue57QhVetCeONwgYvxwtl5cTaGUGcPRu23Lb+kfyV2GMSLmZG9GpitISI8DwduAdTdrm2iJ/gh28N6w8HuM37W7StvPNjGhf5qeIl/h9JeAwGCwKxQCEJ/zh4UFWBdt3dcUHUKZtgJG87ve5iOh0OOp0eAoCorTNWiueSOrZlr+FoeM0kSVHyHh08/w16cM9YNxYNvQD5ifvgq//v3v8fQvMnB8C1M6vuIjmIYZSDwDbqlhHGW8jItT8uaT1uBHAyJX/tLXJ+f8+ijH7KYXSNEhJyOqVF88mzNze99j+eXV7z35hvcvX1KchD59GrhCVPW7DqrR1qiooi6LEikZJhnWNPRNh1JrHlw65Q8y0BqnowW4ASFaSlby6ossRZWqwWRVgzyhLYzlHWFcGCdNwiLxZzBeIxWAte1nuUpvQfirGM6nnB+fs7h4SFt25JEmk5KIqVYLJcMhsOwXxBpRVXVDIYjmqok1pKDUU4aKdq2JZKC1rTMi4ZICdJEkMQRZduy3HTUnUN0jvliA3qGcRE4hYq152dYnzVxXkG7z1H4hSXwJeiZpPgUsu/iKDGBh2icZxx3rq/q7utY9glk/bj1/kyfv93WZIUqceFVul/wUoTcC62sCexSscv8hPngoX+9Zw12hiXEWFjCAhnakGzxDme/ZOL+wup57GJAKX3FpAycDeXY9uPshAxCQZJIOB+yCI+XWAQdO7xj68RZr5pudIQeHTAcHXAwHhEpxboo0UqTZBlFtWH46fd49+SMb6aHKGFZGsVM5JRKcz9LuLr8lC57Gzc65fPsNr/50afcuXWK0wkHo4TDPN6pVAfPMoo0w87xyweCm3LNsnIs0yN+NLjHqgJtDPLghOjoLl1nsHXD+fqcm++8z+dfPONXv/4LvPvWGxxOxmSDBCkcxniXV2uNMx1xEvswT4Y2FNailcIivByg9gK/iYLDUcrX4jOK1vLw6RVl2zEZZmzKClFWRNrQmgblvEPdWpBRhO06is3Gi1KHe5NEmjRNaeuK6XhIlsRUtfbAapayXMzJsgxnLUpKstT3AK7Lgq4uyQLPI4u1F++VgigOgtOmIxK+/sUCN6uC2aqidY4YaGrL/GaJRBMpxWA0oQ0aI0iJNcGQ2CAKxS7zsu/Obz0Lt0vRuhDuGOe5Ho69zEd/b8VPLpvvPZ7erejJYYTQSCoRyGsvhkg9Me0nuglC9LYCj9dY9j92SzjbojC77Mr2bO4nnPfPuX2ljYd3EPbZ994f8+CnbwvZt2awoSDO6ya4QFN3O7wjgE/9PRM6IpreYnjnLfLJMdNME+Uxm6agCxWoJ8cnLDYRm/OPyD86Rt8+w6mM37uc86jUvHz2DkfKcn/9nE+fD5HHL2FPHvCtS8fZjz7m7+iE25MThjpoSIbeY+CJVGkcM+4Kvn4Y8+Fsze8+/JQLlRG/9WtEj3/AIBtRI1GRRtY169WG5bphuXrMerniajbnrTde5a1X7zEdZZjAAq2bhkRJ2ralqiqvhRJi/DiOiaTaDu66KhkPUt4e3aNtDZ8/OaetcmbLFWk+4Pl1hzCaNB3i6JBOYFtHJVvKrmG98qxRvzIbUgSmqZmeHLNar0mjmEQrkiSmKEvKzZo0ianqxlfA4hWvBJYsiYiVJI01WRoTK3/PjPaaLNgOpTVpolHCg5frytB2PiToAGegKxrSZE3TjlBVvGWVWmNA7WEZX2ZX9qFCbyhcYJeGu+e71rtt+OKPCRhFCCuc6wlh/Wv2OCP7537xc/adi/391u2MWf+33cR/8Xv7pz+BF7I1iILedO3/9Wfd/kzjIYT4H4F/F7hwzr0T9h0C/xvwCvA58B86526E/9b/HfC3gQL4T5xzfxje8x8D/1U47X/jnPuHf9Zne/3IHc9ju98RzAIh/eo9CyUcujcaHlL2HooyiM54KywVyXSEvP06ycu/jBocUmyu0ZHBCUHTdh5QE448z9BKcLEp+OjDH5C++g5Ht+7zh+cXLG1E8tLXOJh/wdu6obr+lKcC7O1XaW+/wf/x6R9wZ/hjvnF3BCZFCL3tb9rHtZGU5FHMIWuG9YzFzQwrFM17/zrmlbfQH/w+ebmGYo6ZnXshoyiiMoZPn81Ybr7PbLmibRtef/kuB+MBUirazvhueVFEhtuyQZvG16P0bTudcwyy1DNEnSPLUl67d5fRJOdydkNnBKZrSCJJliRM8jOauqXpHMuixG02TPIBeZKyqWvqxj/SJEUrwdnJAbPlkuVqQRRFHI2GmK5huVoiw+9vTMvRdEpTVbx0eg/T1oGy3te2KJ/JURKc8t0DI18wVzWGddXSBvaoAVoE2vnGXq6tEF2EtWrLVLZYOgwddlt05jNwYfKGeilvHCw4HShDzlde49XdHV6cyjhBh0TvYQkvJkEFOy3z/nUo4RSODguEPjHsdEM6B12fDt6lajww7qv06M2aFRYZlPReWGilv2b9VxChoXsPuvp08/+32Zb/CfjvgX+0t+/vA7/lnPtvhRB/P7z+L4G/BbwRHr8K/A/ArwZj818Dv4K/qt8RQvxj59zNn/XhW2yIPXyJIPwa3D4ZbpzEC74q2PaodULgXITA4OKE9NYp0Su/hrn7DkJn1O0K6gWZ1iihQOE7zNmGysGstayiE7p6yft/8C+I3vwrzOsSxod8OpzyS2nC4vH3+Gbi+O2rD5gf38WlKfVL7/L9i4/56PFDJplkMJ74qtGw+SphbxhXqzlHV4/5G6cDfqsdUI1PMCf3KTtH+kf/FDl7imtqLwKt/CrfdC3P5hXVDz+hqmuWqyX3754wnUyQAlIVMUgTX9kaRpQM+g0CQgrZT7o0iSmKksVmjQUmg4xhmiCdBufl+pabDZfXN4g0garlaDRkmKSMhwPAonTMpiq5Xs4ZjSccj0fMrq+wXct0MqaoKlIlidKcLFFMRiOa1nB5c4MWjqNbJygHjbSsN5Wf6LYFZ5DC1/jEWm6nnnOwLiqWmxoTBrJvqegwzhf/NXXBKM+IlAoC2mHI0HM03DZs8CGKH0c9vtGzSUWgnrptuOIwxhsSP9n/NNe/Dzfkl3aJAM72qWDnjZbw96iz3kB1xnqWcv9de9wkfIc+4rBh7L8QQfXYiggqfCFjtu/p2C+FOT/t9mcaD+fc7wghXvnS7r8L/LXw/B8C/wJvPP4u8I+c94l/TwgxFULcDsf+M+fczP8w8c+Afwf4X/6sz38xhgwEmGCNe91SCeBE6ElhkViv6SE8XqScQI6PiG49wN3/darD11k3BfP1M+rhMXE6xVCAkBg632THwaaVPKxhEWmGWYp78tB3bn/wK1TDCVWU8CPgG7dfZ/nx9/mlfMC/vPyc5ux1Tg+nHB/9Ar/98UMOxkNej1JGgzRYQL/ydNZweTNjPV9yNIr566MJlT7itzcK21i6k/vU0yOS558hsIiQRTJCY6QXKrgqO779o0+4vFnwzuuv8Nor97h76xidxxSVn3AY4xcfpajrehvCAFt6eds2CGeJtAIk1rREUUQUgW1aRpFikyiul0vWVcMwzTjKNUeHGSqOKKuGo4MDDsYR1sJBrpgmJ5yOB5RdR1kJzo6PyNMYpwSmc6w3JXnqJ3aqfRNn51q0lhjTYK0Mk9yrb8U6IY0jhLPQwXzdUDQWr6rvU7fSOToHVWdouxblLAnGA65ul7Hrsxt9aNA56w0P+OfhdWsN1glEAImttVvcpA+Htiv+C9CEv88ei3VfSsLssIc+hBICjAJrDcaZvbDoy+HNzrt5MdXLbo5sGaoy1PR45XWzh/HYQJr8Mjbz02w/K+Zxyzl3Hp4/A26F53eBx3vHfRH2/Wn7/8QmhPh7wN8DGA2ycM13FxrXW2rvdknrWYzCdkhrtlh0TwJzStFMblG+/Kssb3+dq3TE1eU5q8vP2By+wiq+wy/ehruZpllfE23W4Cyb2vDUaCqhGWkYRCV5rmiWj3Hr+zwWb9K5loWBH+spb91+lZP1Fa8tn3IRRfzGa29xLz2iVorfev8zptmQJDohSaKQsYDr1YrPHj6kazru3H6Fucr4myZmZkr+cLHAdDXFg2/glguShz9kWwDo9fURUuCMYtVZPrlccL3+IZ+eP+Nrr7/CW/fvc3QwJosk2nntzzjSxEmEMRbTdSgdYZyj7VqckmR5iooi5ssFGofGcDodcXl5zWCSkWWKw8MRVdmQRjGjOOVgOkRFisZYZjczXjm7j1SaREmKquZmNmdTVQg54uTgyDNhTYtRLoQ8MVVTsdkUVEWDsZY40jR0Pu2MJ6c5E2qWjM+2lY3hZl3ThUyIkoI8FnTWUrfO96NpvecSC0MkFF1YfHqVMNvrdkCoM/E6Hz4c8d5J57xxEpYtyGpDzZINn92Xovnhuccf2YYSoSXqfnZ2m1XxIYgTXltG4nGW7cOYAOz6xXG77RmsHjQVQc0MKbbs2d7T2r0tGGPrf1dPoPtZtp8bMHXOObGvu/bzn+8fAP8A4Ox46j3NsFpI8GInll2bSWMR1oLpoPMcAqF8kOd0SjE54+rlv8zs9GsspeL65oLNZkE7OGGTH0NxxctnA959+23mq2s++v53YW3o4ohFCVIpsmbByG6IIqCoyT7+Fnp8grnzKrareaIjBgd36eolb6U1b28eM13m6Oxl1PSAy3rFdz7zHkgUaQRQViVf/L/tnWuMJFd1x3+nXt3V3fPqndmXd727xsibFTKwEMVWnBglxET+AEIykRESj5AvQUgJfEBYfIJIEYmiKIkUBaJAFCWAzcMKyCKyAoFvyIAJj7W9xuvdNd7Zx+y8e3r6UXXvyYd7q6dtr2Fmws70SPWXWl11qzT1n9NVp+4599z/nb1KlilxfYzGvhmSuEp3bom3VzPWeks8by292j70dfeiJqdy4RlUc1fxrhHGZligUquT1mus9XucuTDL1flF5uYWOf26kxzZ3yTwr59aGlGvVBAVwjgijiMyY1nvdwnjmDiMUONElCpRFWMt9TgmOTCDAtXMUI3WCSYC+tYSEpFZ41TM0pTJWkpmDHkQEkcJfavMHJyhaQz9XgfUEMYB1TCl33dDu2NJhcAasjCAOESMkOcuEAiCyCnCGQuFjq27R2hnGZ089/UM7kHv5W4VtDSEzMJ6J6eX9RivVwizolvgh2OLMMA/8LkqqoJRGeiP5MYQ4We2GtyyHr7HYdS64VzFP8haRCSDMnMoQiWfWBEfGsnGfBT1uY0wCCDHvxB04Kj8e9KXKzAYPXH1X9ZpkxZ5G1d66nprUswy9+s7+zWe3YrXZpDzeImsxRaxXedxTUQOqeoVH5bM+fZZ4OjQeUd82ywbYU7R/t3NXMjfGxtemo1u3KDraK0zSG6wIVgjmErK8vQJLt3yJuabR1k3GXl/nVol5tgtt1CJLa1ei25rkQN6kNDmHGjuR0/dyfnzz7G+bjlchZXFedLeEhU1BGGEsT2y589juh2490GkMYVNUl5IKjRmjjMx+zPecmCKs4vnWEtr1JsHGZu+lTPzZ7ljYZ5GvY4R4dK1OVprbcK0Tn1imjCpkogyk0Br+SLvagb8RzfnhdzSq09iTv4W2lmjMnsetWBVQCIa9Sq1NKXX77m3YhBxbaXN2lPPsrC6yp23n2B/c4L901MEoXt7TtQbg4rGQHwhU+CGr0WEtJqSZRnFzFnj57ek1RrJWEQn64Nm1NIqYRBST1OmGuOEQLvXYW65RRJFHNg35YSEwpC1jkvYmhy6nYwsy/zM2gCMF2lSyPMca82gO23UuiH5yK3vGklAmqa0e0oSRUSBxRilr2BzSANIY1df0+8bOv2cyfEAIffBTaGZ4RzJcBhgcKGKlQCjPhmqbhIlfvGqXC2ZycmtIbOGXC0W9WvAMrg/rVcr3nAiG/ev9zj+/vZJzCIPYYtQqtAdcSOEwwpmxciPDCa/FdcYem4U53WsxRr1WrOy8Vsbg5qN8HU72K7z+AbwPuDT/vvrQ+0fFpGHcQnTFe9gHgf+UkSm/Hn3AQ9t6kpFEuslcV+hp+CrBfMcmxvIciINWZ6YZuXY67l8y5u4Xp1Cs2XqoeXI5BSnDzW4fSIlAJZaLa4vTLCeCdeWl9i3r8mBA4eoNpr86MJFFi+epakt0jQhkohe1mFh0Y2KVBa+B5VJ7O88gB2HrsDlyjivP36SK6sXecNUkyevnMVWx0jGx+nU93NufoVj0106/T6Ly6uEUUwyNkGUNlC1ZOsr0F7m0EQD5hd450zCw5f7XDNCXp9m/eQ9GFUqV19E+n1qjQbNyUm6vS4QEqV10rEJCEO6nTWeenGOxaU2rz12gBOHZzhx62Emx+t0uh3qtbqLs/u5WyQ8txgYSB/keU7Xix+DUokTWu02VtzbOctzqBjq1dRVs9rc1dpEMfW0QiQGLKRxRJZlVOOYXq/H+nqbLCuEgAzGWoJAiP0SilkY0TMZceQSvTbzK86hTsM1CGitrNBebZOEAXEUYW2G8WkF9eI3QeCencwChIRiBm/nYCjfUCQqVMTP41EyY0kkJFcldEMwrk7GGHLreim56iDpqUUJgM/IuhERecV9/Mqp9QycRtELGfBSLxsx3Ib7++jGcOtLBl2tKyoDXx9iDTa3SA7ipRc1CDBBjuTGr+9sNvUY3gibGar9Eq7XMC0il3CjJp8GviwiHwReAP7In/5N3DDtOdxQ7Qf8P74oIn8B/MCf96kiefpLrw3+jbTxYw8mNmkhymLoa47aHlmY0Jo+weprfpOFw6egUqdue9SSKremwr23H+U3DjaJQmh3uyRJiBjL8lqHtbUlrmZdxsb3Ua+Nc+r4bXRW5rh+7RJjtTqBGC7PXmN2dhbT6xFbi/3xd+kcvQOdvGcQW+aTB8kDw9LqFU7WKzx9+eeMVe8krU3x4upFLl25ymq3TZ5DPD5BUhtDseS9Dt3lJYK+K6yyRulcneWdM+M8MrvEUhiSNQ/BqXsJ7beY8qi0IwAABUZJREFUaC3THBsnjCNCa6goxNUK0cQ07ahG2FpG2kssrS1x9uIlri8ssrTa5tTtJ8inGmQIaZKQZT235ILd0HZNkoRqpep0PiNLkDntzyDPWW61iOOY8UaVNHRFXHnuJstFQUQljAnrNXJj6PmqU0QJNCCJEoKgQxxZNw1eA7JOn27mJuFZawlQkigmyzL/MnBiQbkarMRkpk+/36MSCY0KrPQUYwKKZIWgbmlIv2BKzwhdEjRyEyYJ3YLQ+J6sFT9UiuvqB75nkqP01RAUM1txoUqegTVgXB07qq5g0T3v6u5VLRKp4MIkN39bblDNqT5cCnRIc6YoTVAFs9Hbds9EoeUrgyHkIipyMZh1+RkNMUbJjSK59YuABRix5ACZ+ydCs/2ch/x/ui03GyLSAp7dbR6bxDQwv9skNoG9whP2Dte9whNuzPWYqs5s9Q+NdIUp8Kyqvnm3SWwGIvLDvcB1r/CEvcN1r/CEXy/XkV96oUSJEqOJ0nmUKFFiWxh15/HPu01gC9grXPcKT9g7XPcKT/g1ch3phGmJEiVGF6Pe8yhRosSIonQeJUqU2BZG1nmIyB+KyLMics5P+99NLkdF5Dsi8rSIPCUif+bbmyLy3yLynP+e8u0iIv/guf9URE7vMN9QRP5XRB7z+ydE5AnP5xERSXx7xe+f88eP7zDPSRH5qoicFZFnROTuEbbpR/xvf0ZEviQi1VGwq4h8XkTmROTMUNuWbSgi7/PnPydOe+dX4+XTfUfhg1NOeR64DUiAnwCndpHPIeC03x4Dfg6cAv4a+Lhv/zjwV377fuC/cIV/dwFP7DDfjwJfBB7z+18GHvTbnwH+1G9/CPiM334QeGSHef4b8Cd+OwEmR9GmuBngF4B0yJ7vHwW7Ar8LnAbODLVtyYZAEzjvv6f89tSvvPZO3ixbMMjdwOND+w8BD+02ryE+Xwf+AFf9esi3HcIVtQF8Fnj30PmD83aA2xHg28DvAY/5G2UeiF5uW+Bx4G6/HfnzZId4TvgHUl7WPoo2LSQlmt5OjwFvGxW74hT9hp3HlmwIvBv47FD7S857tc+ohi2b1v/Yafgu6BuBJ9i6rslO4O+Aj7Gxms8+YFlV8xtwGfD0x1f8+TuBE8B14F99iPUvIlJnBG2qqrPA3wC/AK7g7PQko2lXuIl6O8MYVecxkhCRBvA14M9VdXX4mDqXvavj3iJSaM0+uZs8NokI193+J1V9I9DGdbEHGAWbAvicwTtwDu8wUMcp4Y08bqYNR9V5vJouyK5BRGKc4/iCqj7qm695PRM2qWtys/HbwNtF5CLwMC50+XtgUkSKeUzDXAY8/fEJYGEHeIJ7u11S1Sf8/ldxzmTUbArwVuCCql5X1Qx4FGfrUbQrbN2G27LtqDqPHwCv9dnsBJd0+sZukREnxPA54BlV/duhQ4WuCbxS1+S9Prt9F17X5GbzVNWHVPWIqh7H2ex/VPU9wHeAB16FZ8H/AX/+jrzpVfUq8KKI3OGbfh94mhGzqccvgLtEpObvhYLryNn1BtffjA0fB+4TkSnfy7rPt/1y7ETCaZtJoPtxoxrPA5/YZS734Lp+PwV+7D/34+LYbwPPAd8Cmv58Af7Rc/8Z8OZd4PwWNkZbbgO+j9NZ+QpQ8e1Vv3/OH79thzm+Afiht+t/4jL9I2lT4JPAWeAM8O9AZRTsihMRvwJkuN7cB7djQ+CPPd9zwAc2c+2yPL1EiRLbwqiGLSVKlBhxlM6jRIkS20LpPEqUKLEtlM6jRIkS20LpPEqUKLEtlM6jRIkS20LpPEqUKLEt/B/CwmMj3EsjcAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_source = cv2.imread(SOURCE_NAME)\n",
    "if image_source is None:\n",
    "    raise ValueError(\"Source image not found\")\n",
    "\n",
    "image_target = cv2.imread(TARGET_NAME)\n",
    "if image_target is None:\n",
    "    raise ValueError(\"Source image not found\")\n",
    "\n",
    "cropped_source = crop_stylegan(image_source)\n",
    "cropped_target = crop_stylegan(image_target)\n",
    "\n",
    "img = cv2.cvtColor(cropped_source, cv2.COLOR_BGR2RGB)\n",
    "plt.imshow(img)\n",
    "plt.title('source')\n",
    "plt.show()\n",
    "\n",
    "img = cv2.cvtColor(cropped_target, cv2.COLOR_BGR2RGB)\n",
    "plt.imshow(img)\n",
    "plt.title('target')\n",
    "plt.show()\n",
    "\n",
    "cv2.imwrite(\"cropped_source.png\", cropped_source)\n",
    "cv2.imwrite(\"cropped_target.png\", cropped_target)\n",
    "\n",
    "#print(find_eyes(cropped_source))\n",
    "#print(find_eyes(cropped_target))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XXf6Sn4cQVIm"
   },
   "source": [
    "The two images are now 1024x1024 and cropped similarly to the ffhq dataset that NVIDIA used to train StyleGAN.\n",
    "\n",
    "## Convert Source to a GAN\n",
    "\n",
    "We will use StyleGAN2, rather than the latest StyleGAN3, because StyleGAN2 contains a projector.py utility that converts images to latent vectors. StyleGAN3 does not have as good support for this [projection](https://github.com/NVlabs/stylegan3/issues/54). First, we convert the source to a GAN latent vector. This process will take several minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "9nMegOhRtpnX",
    "outputId": "a2d91fa9-6007-4f10-fef4-2b54a15a8a6a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading networks from \"https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/ffhq.pkl\"...\n",
      "Downloading https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/ffhq.pkl ... done\n",
      "Computing W midpoint and stddev using 10000 samples...\n",
      "Setting up PyTorch plugin \"bias_act_plugin\"... Done.\n",
      "Downloading https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/metrics/vgg16.pt ... done\n",
      "Setting up PyTorch plugin \"upfirdn2d_plugin\"... Done.\n",
      "step    1/1000: dist 0.69 loss 24568.84\n",
      "step    2/1000: dist 0.68 loss 27642.19\n",
      "step    3/1000: dist 0.69 loss 27167.21\n",
      "step    4/1000: dist 0.64 loss 26253.41\n",
      "step    5/1000: dist 0.68 loss 24959.88\n",
      "step    6/1000: dist 0.67 loss 23356.19\n",
      "step    7/1000: dist 0.68 loss 21512.25\n",
      "step    8/1000: dist 0.64 loss 19487.28\n",
      "step    9/1000: dist 0.65 loss 17341.38\n",
      "step   10/1000: dist 0.64 loss 15140.43\n",
      "step   11/1000: dist 0.69 loss 12949.55\n",
      "step   12/1000: dist 0.66 loss 10820.28\n",
      "step   13/1000: dist 0.67 loss 8802.95\n",
      "step   14/1000: dist 0.70 loss 6946.31\n",
      "step   15/1000: dist 0.68 loss 5316.80\n",
      "step   16/1000: dist 0.59 loss 3971.21\n",
      "step   17/1000: dist 0.59 loss 2941.14\n",
      "step   18/1000: dist 0.66 loss 2216.37\n",
      "step   19/1000: dist 0.63 loss 1758.90\n",
      "step   20/1000: dist 0.61 loss 1567.61\n",
      "step   21/1000: dist 0.58 loss 1602.35\n",
      "step   22/1000: dist 0.56 loss 1787.89\n",
      "step   23/1000: dist 0.57 loss 2053.43\n",
      "step   24/1000: dist 0.57 loss 2327.65\n",
      "step   25/1000: dist 0.55 loss 2538.83\n",
      "step   26/1000: dist 0.57 loss 2637.41\n",
      "step   27/1000: dist 0.56 loss 2603.98\n",
      "step   28/1000: dist 0.55 loss 2477.22\n",
      "step   29/1000: dist 0.56 loss 2317.67\n",
      "step   30/1000: dist 0.56 loss 2120.18\n",
      "step   31/1000: dist 0.55 loss 1884.70\n",
      "step   32/1000: dist 0.57 loss 1628.14\n",
      "step   33/1000: dist 0.57 loss 1388.85\n",
      "step   34/1000: dist 0.55 loss 1184.02\n",
      "step   35/1000: dist 0.56 loss 1026.62\n",
      "step   36/1000: dist 0.54 loss 909.77\n",
      "step   37/1000: dist 0.55 loss 830.95\n",
      "step   38/1000: dist 0.55 loss 805.37\n",
      "step   39/1000: dist 0.53 loss 812.69\n",
      "step   40/1000: dist 0.53 loss 834.78\n",
      "step   41/1000: dist 0.52 loss 828.74\n",
      "step   42/1000: dist 0.53 loss 761.30\n",
      "step   43/1000: dist 0.56 loss 651.21\n",
      "step   44/1000: dist 0.52 loss 521.51\n",
      "step   45/1000: dist 0.50 loss 402.90\n",
      "step   46/1000: dist 0.50 loss 318.31\n",
      "step   47/1000: dist 0.55 loss 263.56\n",
      "step   48/1000: dist 0.53 loss 241.12\n",
      "step   49/1000: dist 0.49 loss 251.14\n",
      "step   50/1000: dist 0.51 loss 304.16\n",
      "step   51/1000: dist 0.50 loss 369.90\n",
      "step   52/1000: dist 0.52 loss 402.65\n",
      "step   53/1000: dist 0.53 loss 403.27\n",
      "step   54/1000: dist 0.54 loss 373.34\n",
      "step   55/1000: dist 0.48 loss 286.43\n",
      "step   56/1000: dist 0.49 loss 204.31\n",
      "step   57/1000: dist 0.48 loss 142.15\n",
      "step   58/1000: dist 0.49 loss 72.53\n",
      "step   59/1000: dist 0.49 loss 64.59\n",
      "step   60/1000: dist 0.49 loss 60.36\n",
      "step   61/1000: dist 0.48 loss 57.51\n",
      "step   62/1000: dist 0.48 loss 96.37\n",
      "step   63/1000: dist 0.49 loss 109.48\n",
      "step   64/1000: dist 0.47 loss 129.66\n",
      "step   65/1000: dist 0.49 loss 132.66\n",
      "step   66/1000: dist 0.49 loss 117.68\n",
      "step   67/1000: dist 0.48 loss 103.61\n",
      "step   68/1000: dist 0.49 loss 69.93\n",
      "step   69/1000: dist 0.47 loss 52.00\n",
      "step   70/1000: dist 0.48 loss 27.73\n",
      "step   71/1000: dist 0.47 loss 19.48\n",
      "step   72/1000: dist 0.47 loss 19.65\n",
      "step   73/1000: dist 0.47 loss 20.25\n",
      "step   74/1000: dist 0.47 loss 29.61\n",
      "step   75/1000: dist 0.47 loss 33.64\n",
      "step   76/1000: dist 0.46 loss 39.67\n",
      "step   77/1000: dist 0.47 loss 36.08\n",
      "step   78/1000: dist 0.46 loss 32.92\n",
      "step   79/1000: dist 0.46 loss 31.11\n",
      "step   80/1000: dist 0.47 loss 26.28\n",
      "step   81/1000: dist 0.48 loss 22.76\n",
      "step   82/1000: dist 0.48 loss 13.80\n",
      "step   83/1000: dist 0.46 loss 12.49\n",
      "step   84/1000: dist 0.48 loss 16.18\n",
      "step   85/1000: dist 0.45 loss 15.87\n",
      "step   86/1000: dist 0.44 loss 12.29\n",
      "step   87/1000: dist 0.46 loss 10.47\n",
      "step   88/1000: dist 0.48 loss 12.08\n",
      "step   89/1000: dist 0.46 loss 10.22\n",
      "step   90/1000: dist 0.45 loss 7.48 \n",
      "step   91/1000: dist 0.49 loss 6.97 \n",
      "step   92/1000: dist 0.45 loss 6.56 \n",
      "step   93/1000: dist 0.48 loss 7.02 \n",
      "step   94/1000: dist 0.46 loss 8.58 \n",
      "step   95/1000: dist 0.45 loss 10.76\n",
      "step   96/1000: dist 0.47 loss 12.40\n",
      "step   97/1000: dist 0.48 loss 11.84\n",
      "step   98/1000: dist 0.45 loss 9.08 \n",
      "step   99/1000: dist 0.45 loss 6.71 \n",
      "step  100/1000: dist 0.45 loss 7.39 \n",
      "step  101/1000: dist 0.43 loss 9.75 \n",
      "step  102/1000: dist 0.43 loss 9.56 \n",
      "step  103/1000: dist 0.43 loss 5.58 \n",
      "step  104/1000: dist 0.44 loss 2.44 \n",
      "step  105/1000: dist 0.44 loss 4.01 \n",
      "step  106/1000: dist 0.45 loss 7.38 \n",
      "step  107/1000: dist 0.43 loss 8.32 \n",
      "step  108/1000: dist 0.43 loss 6.85 \n",
      "step  109/1000: dist 0.42 loss 5.39 \n",
      "step  110/1000: dist 0.44 loss 5.18 \n",
      "step  111/1000: dist 0.45 loss 5.21 \n",
      "step  112/1000: dist 0.43 loss 4.84 \n",
      "step  113/1000: dist 0.44 loss 4.69 \n",
      "step  114/1000: dist 0.43 loss 5.06 \n",
      "step  115/1000: dist 0.43 loss 5.76 \n",
      "step  116/1000: dist 0.42 loss 6.62 \n",
      "step  117/1000: dist 0.43 loss 7.34 \n",
      "step  118/1000: dist 0.44 loss 7.84 \n",
      "step  119/1000: dist 0.42 loss 9.06 \n",
      "step  120/1000: dist 0.44 loss 11.57\n",
      "step  121/1000: dist 0.43 loss 12.81\n",
      "step  122/1000: dist 0.42 loss 8.81 \n",
      "step  123/1000: dist 0.43 loss 2.64 \n",
      "step  124/1000: dist 0.41 loss 2.90 \n",
      "step  125/1000: dist 0.42 loss 7.96 \n",
      "step  126/1000: dist 0.41 loss 8.38 \n",
      "step  127/1000: dist 0.43 loss 3.88 \n",
      "step  128/1000: dist 0.42 loss 2.75 \n",
      "step  129/1000: dist 0.41 loss 4.95 \n",
      "step  130/1000: dist 0.42 loss 4.01 \n",
      "step  131/1000: dist 0.42 loss 1.47 \n",
      "step  132/1000: dist 0.43 loss 2.52 \n",
      "step  133/1000: dist 0.41 loss 4.18 \n",
      "step  134/1000: dist 0.40 loss 3.20 \n",
      "step  135/1000: dist 0.42 loss 3.41 \n",
      "step  136/1000: dist 0.41 loss 6.76 \n",
      "step  137/1000: dist 0.44 loss 10.63\n",
      "step  138/1000: dist 0.42 loss 14.50\n",
      "step  139/1000: dist 0.41 loss 15.30\n",
      "step  140/1000: dist 0.42 loss 8.50 \n",
      "step  141/1000: dist 0.42 loss 3.20 \n",
      "step  142/1000: dist 0.41 loss 8.34 \n",
      "step  143/1000: dist 0.40 loss 13.73\n",
      "step  144/1000: dist 0.40 loss 11.53\n",
      "step  145/1000: dist 0.41 loss 13.75\n",
      "step  146/1000: dist 0.39 loss 23.21\n",
      "step  147/1000: dist 0.42 loss 23.69\n",
      "step  148/1000: dist 0.41 loss 13.22\n",
      "step  149/1000: dist 0.40 loss 7.29 \n",
      "step  150/1000: dist 0.42 loss 8.80 \n",
      "step  151/1000: dist 0.42 loss 10.39\n",
      "step  152/1000: dist 0.41 loss 10.74\n",
      "step  153/1000: dist 0.39 loss 10.47\n",
      "step  154/1000: dist 0.40 loss 12.42\n",
      "step  155/1000: dist 0.40 loss 20.22\n",
      "step  156/1000: dist 0.40 loss 27.15\n",
      "step  157/1000: dist 0.39 loss 24.20\n",
      "step  158/1000: dist 0.42 loss 17.26\n",
      "step  159/1000: dist 0.40 loss 14.65\n",
      "step  160/1000: dist 0.40 loss 13.90\n",
      "step  161/1000: dist 0.40 loss 13.30\n",
      "step  162/1000: dist 0.39 loss 15.58\n",
      "step  163/1000: dist 0.41 loss 20.83\n",
      "step  164/1000: dist 0.41 loss 22.71\n",
      "step  165/1000: dist 0.43 loss 19.80\n",
      "step  166/1000: dist 0.40 loss 17.83\n",
      "step  167/1000: dist 0.39 loss 17.91\n",
      "step  168/1000: dist 0.40 loss 14.52\n",
      "step  169/1000: dist 0.40 loss 10.05\n",
      "step  170/1000: dist 0.39 loss 8.76 \n",
      "step  171/1000: dist 0.38 loss 7.54 \n",
      "step  172/1000: dist 0.40 loss 7.03 \n",
      "step  173/1000: dist 0.38 loss 9.81 \n",
      "step  174/1000: dist 0.40 loss 9.86 \n",
      "step  175/1000: dist 0.41 loss 4.71 \n",
      "step  176/1000: dist 0.39 loss 2.85 \n",
      "step  177/1000: dist 0.39 loss 5.94 \n",
      "step  178/1000: dist 0.41 loss 6.41 \n",
      "step  179/1000: dist 0.39 loss 3.66 \n",
      "step  180/1000: dist 0.39 loss 2.83 \n",
      "step  181/1000: dist 0.40 loss 3.92 \n",
      "step  182/1000: dist 0.41 loss 4.22 \n",
      "step  183/1000: dist 0.38 loss 3.22 \n",
      "step  184/1000: dist 0.39 loss 2.18 \n",
      "step  185/1000: dist 0.39 loss 2.63 \n",
      "step  186/1000: dist 0.38 loss 4.38 \n",
      "step  187/1000: dist 0.38 loss 5.70 \n",
      "step  188/1000: dist 0.39 loss 7.27 \n",
      "step  189/1000: dist 0.40 loss 11.58\n",
      "step  190/1000: dist 0.38 loss 18.20\n",
      "step  191/1000: dist 0.38 loss 22.91\n",
      "step  192/1000: dist 0.38 loss 19.88\n",
      "step  193/1000: dist 0.40 loss 10.03\n",
      "step  194/1000: dist 0.38 loss 7.92 \n",
      "step  195/1000: dist 0.39 loss 16.66\n",
      "step  196/1000: dist 0.39 loss 19.63\n",
      "step  197/1000: dist 0.38 loss 12.89\n",
      "step  198/1000: dist 0.38 loss 13.33\n",
      "step  199/1000: dist 0.38 loss 20.81\n",
      "step  200/1000: dist 0.38 loss 17.69\n",
      "step  201/1000: dist 0.39 loss 7.83 \n",
      "step  202/1000: dist 0.39 loss 6.01 \n",
      "step  203/1000: dist 0.36 loss 7.21 \n",
      "step  204/1000: dist 0.39 loss 6.24 \n",
      "step  205/1000: dist 0.38 loss 8.44 \n",
      "step  206/1000: dist 0.38 loss 9.41 \n",
      "step  207/1000: dist 0.38 loss 4.84 \n",
      "step  208/1000: dist 0.37 loss 3.23 \n",
      "step  209/1000: dist 0.38 loss 6.27 \n",
      "step  210/1000: dist 0.37 loss 8.15 \n",
      "step  211/1000: dist 0.37 loss 10.04\n",
      "step  212/1000: dist 0.38 loss 11.97\n",
      "step  213/1000: dist 0.38 loss 11.18\n",
      "step  214/1000: dist 0.37 loss 9.16 \n",
      "step  215/1000: dist 0.38 loss 6.61 \n",
      "step  216/1000: dist 0.37 loss 3.30 \n",
      "step  217/1000: dist 0.37 loss 3.33 \n",
      "step  218/1000: dist 0.37 loss 6.29 \n",
      "step  219/1000: dist 0.37 loss 6.12 \n",
      "step  220/1000: dist 0.36 loss 3.18 \n",
      "step  221/1000: dist 0.37 loss 2.60 \n",
      "step  222/1000: dist 0.37 loss 4.20 \n",
      "step  223/1000: dist 0.37 loss 5.04 \n",
      "step  224/1000: dist 0.37 loss 4.37 \n",
      "step  225/1000: dist 0.37 loss 3.59 \n",
      "step  226/1000: dist 0.37 loss 4.55 \n",
      "step  227/1000: dist 0.37 loss 6.34 \n",
      "step  228/1000: dist 0.37 loss 5.99 \n",
      "step  229/1000: dist 0.37 loss 3.80 \n",
      "step  230/1000: dist 0.37 loss 2.65 \n",
      "step  231/1000: dist 0.36 loss 2.51 \n",
      "step  232/1000: dist 0.37 loss 1.80 \n",
      "step  233/1000: dist 0.37 loss 1.14 \n",
      "step  234/1000: dist 0.37 loss 1.69 \n",
      "step  235/1000: dist 0.37 loss 2.71 \n",
      "step  236/1000: dist 0.37 loss 2.88 \n",
      "step  237/1000: dist 0.36 loss 2.07 \n",
      "step  238/1000: dist 0.37 loss 1.26 \n",
      "step  239/1000: dist 0.36 loss 1.30 \n",
      "step  240/1000: dist 0.37 loss 2.15 \n",
      "step  241/1000: dist 0.36 loss 3.45 \n",
      "step  242/1000: dist 0.36 loss 5.85 \n",
      "step  243/1000: dist 0.36 loss 10.44\n",
      "step  244/1000: dist 0.36 loss 16.26\n",
      "step  245/1000: dist 0.37 loss 18.68\n",
      "step  246/1000: dist 0.37 loss 11.90\n",
      "step  247/1000: dist 0.37 loss 2.40 \n",
      "step  248/1000: dist 0.36 loss 2.70 \n",
      "step  249/1000: dist 0.36 loss 10.08\n",
      "step  250/1000: dist 0.38 loss 11.57\n",
      "step  251/1000: dist 0.36 loss 8.12 \n",
      "step  252/1000: dist 0.35 loss 13.61\n",
      "step  253/1000: dist 0.35 loss 25.04\n",
      "step  254/1000: dist 0.36 loss 24.02\n",
      "step  255/1000: dist 0.36 loss 9.58 \n",
      "step  256/1000: dist 0.36 loss 2.80 \n",
      "step  257/1000: dist 0.36 loss 9.33 \n",
      "step  258/1000: dist 0.36 loss 12.41\n",
      "step  259/1000: dist 0.35 loss 6.26 \n",
      "step  260/1000: dist 0.37 loss 3.37 \n",
      "step  261/1000: dist 0.35 loss 7.18 \n",
      "step  262/1000: dist 0.36 loss 6.98 \n",
      "step  263/1000: dist 0.36 loss 3.34 \n",
      "step  264/1000: dist 0.36 loss 5.19 \n",
      "step  265/1000: dist 0.36 loss 8.05 \n",
      "step  266/1000: dist 0.36 loss 7.96 \n",
      "step  267/1000: dist 0.36 loss 12.16\n",
      "step  268/1000: dist 0.36 loss 18.35\n",
      "step  269/1000: dist 0.37 loss 17.42\n",
      "step  270/1000: dist 0.37 loss 10.68\n",
      "step  271/1000: dist 0.36 loss 4.65 \n",
      "step  272/1000: dist 0.36 loss 3.72 \n",
      "step  273/1000: dist 0.37 loss 9.11 \n",
      "step  274/1000: dist 0.36 loss 11.94\n",
      "step  275/1000: dist 0.36 loss 7.31 \n",
      "step  276/1000: dist 0.36 loss 7.62 \n",
      "step  277/1000: dist 0.35 loss 16.34\n",
      "step  278/1000: dist 0.35 loss 22.40\n",
      "step  279/1000: dist 0.35 loss 25.18\n",
      "step  280/1000: dist 0.35 loss 28.86\n",
      "step  281/1000: dist 0.36 loss 28.18\n",
      "step  282/1000: dist 0.37 loss 24.31\n",
      "step  283/1000: dist 0.36 loss 24.22\n",
      "step  284/1000: dist 0.35 loss 24.12\n",
      "step  285/1000: dist 0.35 loss 21.50\n",
      "step  286/1000: dist 0.35 loss 22.67\n",
      "step  287/1000: dist 0.36 loss 28.68\n",
      "step  288/1000: dist 0.34 loss 29.07\n",
      "step  289/1000: dist 0.37 loss 19.28\n",
      "step  290/1000: dist 0.36 loss 13.45\n",
      "step  291/1000: dist 0.35 loss 19.68\n",
      "step  292/1000: dist 0.35 loss 26.27\n",
      "step  293/1000: dist 0.35 loss 25.12\n",
      "step  294/1000: dist 0.35 loss 21.81\n",
      "step  295/1000: dist 0.36 loss 22.30\n",
      "step  296/1000: dist 0.35 loss 26.51\n",
      "step  297/1000: dist 0.36 loss 29.40\n",
      "step  298/1000: dist 0.35 loss 25.66\n",
      "step  299/1000: dist 0.34 loss 20.94\n",
      "step  300/1000: dist 0.34 loss 22.96\n",
      "step  301/1000: dist 0.34 loss 24.71\n",
      "step  302/1000: dist 0.35 loss 20.26\n",
      "step  303/1000: dist 0.36 loss 14.66\n",
      "step  304/1000: dist 0.35 loss 10.48\n",
      "step  305/1000: dist 0.34 loss 8.68 \n",
      "step  306/1000: dist 0.34 loss 12.03\n",
      "step  307/1000: dist 0.34 loss 14.06\n",
      "step  308/1000: dist 0.35 loss 7.56 \n",
      "step  309/1000: dist 0.35 loss 2.77 \n",
      "step  310/1000: dist 0.35 loss 7.47 \n",
      "step  311/1000: dist 0.35 loss 10.36\n",
      "step  312/1000: dist 0.34 loss 5.24 \n",
      "step  313/1000: dist 0.35 loss 2.05 \n",
      "step  314/1000: dist 0.34 loss 5.11 \n",
      "step  315/1000: dist 0.35 loss 7.07 \n",
      "step  316/1000: dist 0.35 loss 5.08 \n",
      "step  317/1000: dist 0.34 loss 4.33 \n",
      "step  318/1000: dist 0.35 loss 7.67 \n",
      "step  319/1000: dist 0.34 loss 12.37\n",
      "step  320/1000: dist 0.34 loss 16.78\n",
      "step  321/1000: dist 0.35 loss 20.85\n",
      "step  322/1000: dist 0.34 loss 21.44\n",
      "step  323/1000: dist 0.33 loss 16.52\n",
      "step  324/1000: dist 0.33 loss 14.56\n",
      "step  325/1000: dist 0.34 loss 18.90\n",
      "step  326/1000: dist 0.34 loss 18.37\n",
      "step  327/1000: dist 0.35 loss 8.28 \n",
      "step  328/1000: dist 0.34 loss 2.29 \n",
      "step  329/1000: dist 0.35 loss 8.59 \n",
      "step  330/1000: dist 0.34 loss 13.68\n",
      "step  331/1000: dist 0.34 loss 7.50 \n",
      "step  332/1000: dist 0.35 loss 1.79 \n",
      "step  333/1000: dist 0.35 loss 5.54 \n",
      "step  334/1000: dist 0.34 loss 8.76 \n",
      "step  335/1000: dist 0.35 loss 5.35 \n",
      "step  336/1000: dist 0.34 loss 3.83 \n",
      "step  337/1000: dist 0.33 loss 7.30 \n",
      "step  338/1000: dist 0.34 loss 9.16 \n",
      "step  339/1000: dist 0.34 loss 9.84 \n",
      "step  340/1000: dist 0.35 loss 14.98\n",
      "step  341/1000: dist 0.34 loss 21.81\n",
      "step  342/1000: dist 0.34 loss 25.12\n",
      "step  343/1000: dist 0.34 loss 24.57\n",
      "step  344/1000: dist 0.34 loss 20.08\n",
      "step  345/1000: dist 0.34 loss 13.54\n",
      "step  346/1000: dist 0.35 loss 13.06\n",
      "step  347/1000: dist 0.34 loss 19.40\n",
      "step  348/1000: dist 0.33 loss 20.69\n",
      "step  349/1000: dist 0.33 loss 10.90\n",
      "step  350/1000: dist 0.33 loss 2.13 \n",
      "step  351/1000: dist 0.35 loss 5.08 \n",
      "step  352/1000: dist 0.34 loss 12.02\n",
      "step  353/1000: dist 0.34 loss 11.44\n",
      "step  354/1000: dist 0.34 loss 6.04 \n",
      "step  355/1000: dist 0.34 loss 5.80 \n",
      "step  356/1000: dist 0.34 loss 11.18\n",
      "step  357/1000: dist 0.34 loss 16.00\n",
      "step  358/1000: dist 0.34 loss 18.66\n",
      "step  359/1000: dist 0.34 loss 18.86\n",
      "step  360/1000: dist 0.33 loss 13.73\n",
      "step  361/1000: dist 0.33 loss 5.32 \n",
      "step  362/1000: dist 0.34 loss 3.06 \n",
      "step  363/1000: dist 0.33 loss 7.89 \n",
      "step  364/1000: dist 0.33 loss 10.21\n",
      "step  365/1000: dist 0.33 loss 5.65 \n",
      "step  366/1000: dist 0.32 loss 1.92 \n",
      "step  367/1000: dist 0.34 loss 4.22 \n",
      "step  368/1000: dist 0.33 loss 6.29 \n",
      "step  369/1000: dist 0.33 loss 3.76 \n",
      "step  370/1000: dist 0.33 loss 1.72 \n",
      "step  371/1000: dist 0.33 loss 3.26 \n",
      "step  372/1000: dist 0.33 loss 3.86 \n",
      "step  373/1000: dist 0.34 loss 1.95 \n",
      "step  374/1000: dist 0.33 loss 1.59 \n",
      "step  375/1000: dist 0.33 loss 2.97 \n",
      "step  376/1000: dist 0.32 loss 2.49 \n",
      "step  377/1000: dist 0.33 loss 1.11 \n",
      "step  378/1000: dist 0.32 loss 1.87 \n",
      "step  379/1000: dist 0.34 loss 3.21 \n",
      "step  380/1000: dist 0.33 loss 3.13 \n",
      "step  381/1000: dist 0.33 loss 4.06 \n",
      "step  382/1000: dist 0.32 loss 7.84 \n",
      "step  383/1000: dist 0.32 loss 13.22\n",
      "step  384/1000: dist 0.32 loss 19.29\n",
      "step  385/1000: dist 0.32 loss 23.98\n",
      "step  386/1000: dist 0.33 loss 21.28\n",
      "step  387/1000: dist 0.33 loss 13.27\n",
      "step  388/1000: dist 0.33 loss 12.23\n",
      "step  389/1000: dist 0.32 loss 21.08\n",
      "step  390/1000: dist 0.32 loss 27.59\n",
      "step  391/1000: dist 0.32 loss 24.08\n",
      "step  392/1000: dist 0.32 loss 17.60\n",
      "step  393/1000: dist 0.33 loss 14.27\n",
      "step  394/1000: dist 0.33 loss 11.27\n",
      "step  395/1000: dist 0.33 loss 8.59 \n",
      "step  396/1000: dist 0.32 loss 9.70 \n",
      "step  397/1000: dist 0.33 loss 11.47\n",
      "step  398/1000: dist 0.32 loss 7.58 \n",
      "step  399/1000: dist 0.32 loss 3.13 \n",
      "step  400/1000: dist 0.32 loss 5.77 \n",
      "step  401/1000: dist 0.32 loss 9.09 \n",
      "step  402/1000: dist 0.32 loss 5.23 \n",
      "step  403/1000: dist 0.33 loss 1.28 \n",
      "step  404/1000: dist 0.32 loss 3.82 \n",
      "step  405/1000: dist 0.32 loss 5.91 \n",
      "step  406/1000: dist 0.32 loss 3.10 \n",
      "step  407/1000: dist 0.32 loss 1.62 \n",
      "step  408/1000: dist 0.32 loss 3.26 \n",
      "step  409/1000: dist 0.32 loss 3.00 \n",
      "step  410/1000: dist 0.32 loss 1.46 \n",
      "step  411/1000: dist 0.32 loss 2.15 \n",
      "step  412/1000: dist 0.32 loss 2.80 \n",
      "step  413/1000: dist 0.32 loss 1.41 \n",
      "step  414/1000: dist 0.32 loss 0.93 \n",
      "step  415/1000: dist 0.31 loss 2.13 \n",
      "step  416/1000: dist 0.32 loss 2.36 \n",
      "step  417/1000: dist 0.33 loss 1.89 \n",
      "step  418/1000: dist 0.32 loss 2.89 \n",
      "step  419/1000: dist 0.32 loss 5.33 \n",
      "step  420/1000: dist 0.32 loss 9.25 \n",
      "step  421/1000: dist 0.33 loss 16.09\n",
      "step  422/1000: dist 0.32 loss 24.57\n",
      "step  423/1000: dist 0.32 loss 26.95\n",
      "step  424/1000: dist 0.31 loss 19.15\n",
      "step  425/1000: dist 0.32 loss 11.93\n",
      "step  426/1000: dist 0.32 loss 17.14\n",
      "step  427/1000: dist 0.31 loss 23.52\n",
      "step  428/1000: dist 0.32 loss 15.46\n",
      "step  429/1000: dist 0.31 loss 3.44 \n",
      "step  430/1000: dist 0.32 loss 6.88 \n",
      "step  431/1000: dist 0.31 loss 17.01\n",
      "step  432/1000: dist 0.31 loss 16.33\n",
      "step  433/1000: dist 0.31 loss 11.61\n",
      "step  434/1000: dist 0.31 loss 13.26\n",
      "step  435/1000: dist 0.31 loss 13.25\n",
      "step  436/1000: dist 0.31 loss 7.99 \n",
      "step  437/1000: dist 0.31 loss 5.13 \n",
      "step  438/1000: dist 0.31 loss 4.27 \n",
      "step  439/1000: dist 0.31 loss 3.72 \n",
      "step  440/1000: dist 0.31 loss 6.71 \n",
      "step  441/1000: dist 0.31 loss 7.85 \n",
      "step  442/1000: dist 0.32 loss 3.05 \n",
      "step  443/1000: dist 0.31 loss 1.01 \n",
      "step  444/1000: dist 0.31 loss 3.84 \n",
      "step  445/1000: dist 0.31 loss 4.11 \n",
      "step  446/1000: dist 0.31 loss 2.56 \n",
      "step  447/1000: dist 0.32 loss 2.66 \n",
      "step  448/1000: dist 0.31 loss 2.22 \n",
      "step  449/1000: dist 0.31 loss 1.51 \n",
      "step  450/1000: dist 0.31 loss 2.12 \n",
      "step  451/1000: dist 0.31 loss 2.16 \n",
      "step  452/1000: dist 0.31 loss 1.58 \n",
      "step  453/1000: dist 0.31 loss 1.72 \n",
      "step  454/1000: dist 0.31 loss 1.64 \n",
      "step  455/1000: dist 0.31 loss 1.62 \n",
      "step  456/1000: dist 0.31 loss 2.54 \n",
      "step  457/1000: dist 0.31 loss 3.23 \n",
      "step  458/1000: dist 0.31 loss 4.01 \n",
      "step  459/1000: dist 0.31 loss 6.42 \n",
      "step  460/1000: dist 0.31 loss 9.23 \n",
      "step  461/1000: dist 0.31 loss 10.20\n",
      "step  462/1000: dist 0.31 loss 8.64 \n",
      "step  463/1000: dist 0.31 loss 4.75 \n",
      "step  464/1000: dist 0.31 loss 1.29 \n",
      "step  465/1000: dist 0.31 loss 1.23 \n",
      "step  466/1000: dist 0.31 loss 3.58 \n",
      "step  467/1000: dist 0.30 loss 4.88 \n",
      "step  468/1000: dist 0.31 loss 3.58 \n",
      "step  469/1000: dist 0.31 loss 1.32 \n",
      "step  470/1000: dist 0.31 loss 0.72 \n",
      "step  471/1000: dist 0.31 loss 2.10 \n",
      "step  472/1000: dist 0.31 loss 3.09 \n",
      "step  473/1000: dist 0.31 loss 2.07 \n",
      "step  474/1000: dist 0.31 loss 0.66 \n",
      "step  475/1000: dist 0.31 loss 0.85 \n",
      "step  476/1000: dist 0.31 loss 1.94 \n",
      "step  477/1000: dist 0.30 loss 2.23 \n",
      "step  478/1000: dist 0.30 loss 1.61 \n",
      "step  479/1000: dist 0.31 loss 1.47 \n",
      "step  480/1000: dist 0.31 loss 2.64 \n",
      "step  481/1000: dist 0.31 loss 4.61 \n",
      "step  482/1000: dist 0.31 loss 6.94 \n",
      "step  483/1000: dist 0.31 loss 10.78\n",
      "step  484/1000: dist 0.31 loss 18.04\n",
      "step  485/1000: dist 0.31 loss 29.05\n",
      "step  486/1000: dist 0.31 loss 40.36\n",
      "step  487/1000: dist 0.30 loss 43.49\n",
      "step  488/1000: dist 0.30 loss 35.09\n",
      "step  489/1000: dist 0.30 loss 29.96\n",
      "step  490/1000: dist 0.31 loss 43.41\n",
      "step  491/1000: dist 0.31 loss 56.04\n",
      "step  492/1000: dist 0.30 loss 38.46\n",
      "step  493/1000: dist 0.30 loss 8.22 \n",
      "step  494/1000: dist 0.30 loss 9.72 \n",
      "step  495/1000: dist 0.30 loss 29.15\n",
      "step  496/1000: dist 0.30 loss 23.73\n",
      "step  497/1000: dist 0.30 loss 7.04 \n",
      "step  498/1000: dist 0.30 loss 13.43\n",
      "step  499/1000: dist 0.30 loss 23.59\n",
      "step  500/1000: dist 0.30 loss 17.84\n",
      "step  501/1000: dist 0.30 loss 19.33\n",
      "step  502/1000: dist 0.30 loss 28.43\n",
      "step  503/1000: dist 0.30 loss 21.12\n",
      "step  504/1000: dist 0.30 loss 9.01 \n",
      "step  505/1000: dist 0.30 loss 8.26 \n",
      "step  506/1000: dist 0.30 loss 9.52 \n",
      "step  507/1000: dist 0.30 loss 13.00\n",
      "step  508/1000: dist 0.30 loss 17.64\n",
      "step  509/1000: dist 0.31 loss 14.73\n",
      "step  510/1000: dist 0.30 loss 19.13\n",
      "step  511/1000: dist 0.30 loss 33.71\n",
      "step  512/1000: dist 0.30 loss 31.12\n",
      "step  513/1000: dist 0.31 loss 13.14\n",
      "step  514/1000: dist 0.30 loss 6.40 \n",
      "step  515/1000: dist 0.30 loss 14.30\n",
      "step  516/1000: dist 0.30 loss 24.06\n",
      "step  517/1000: dist 0.30 loss 24.87\n",
      "step  518/1000: dist 0.30 loss 23.05\n",
      "step  519/1000: dist 0.30 loss 30.82\n",
      "step  520/1000: dist 0.30 loss 35.43\n",
      "step  521/1000: dist 0.30 loss 30.63\n",
      "step  522/1000: dist 0.30 loss 34.11\n",
      "step  523/1000: dist 0.30 loss 39.74\n",
      "step  524/1000: dist 0.30 loss 28.25\n",
      "step  525/1000: dist 0.30 loss 11.24\n",
      "step  526/1000: dist 0.30 loss 9.98 \n",
      "step  527/1000: dist 0.30 loss 17.81\n",
      "step  528/1000: dist 0.30 loss 18.88\n",
      "step  529/1000: dist 0.30 loss 12.85\n",
      "step  530/1000: dist 0.30 loss 9.04 \n",
      "step  531/1000: dist 0.29 loss 13.49\n",
      "step  532/1000: dist 0.30 loss 22.25\n",
      "step  533/1000: dist 0.29 loss 28.80\n",
      "step  534/1000: dist 0.30 loss 33.04\n",
      "step  535/1000: dist 0.29 loss 32.25\n",
      "step  536/1000: dist 0.30 loss 19.49\n",
      "step  537/1000: dist 0.29 loss 6.74 \n",
      "step  538/1000: dist 0.29 loss 11.76\n",
      "step  539/1000: dist 0.29 loss 22.10\n",
      "step  540/1000: dist 0.29 loss 17.26\n",
      "step  541/1000: dist 0.29 loss 13.31\n",
      "step  542/1000: dist 0.29 loss 26.46\n",
      "step  543/1000: dist 0.29 loss 37.41\n",
      "step  544/1000: dist 0.29 loss 37.61\n",
      "step  545/1000: dist 0.30 loss 35.10\n",
      "step  546/1000: dist 0.29 loss 20.96\n",
      "step  547/1000: dist 0.29 loss 4.67 \n",
      "step  548/1000: dist 0.29 loss 9.04 \n",
      "step  549/1000: dist 0.29 loss 18.12\n",
      "step  550/1000: dist 0.29 loss 13.05\n",
      "step  551/1000: dist 0.29 loss 7.97 \n",
      "step  552/1000: dist 0.29 loss 8.73 \n",
      "step  553/1000: dist 0.29 loss 7.92 \n",
      "step  554/1000: dist 0.29 loss 6.70 \n",
      "step  555/1000: dist 0.29 loss 5.97 \n",
      "step  556/1000: dist 0.29 loss 6.93 \n",
      "step  557/1000: dist 0.29 loss 7.92 \n",
      "step  558/1000: dist 0.29 loss 5.14 \n",
      "step  559/1000: dist 0.29 loss 6.64 \n",
      "step  560/1000: dist 0.29 loss 13.24\n",
      "step  561/1000: dist 0.29 loss 15.03\n",
      "step  562/1000: dist 0.29 loss 16.70\n",
      "step  563/1000: dist 0.29 loss 20.20\n",
      "step  564/1000: dist 0.29 loss 16.17\n",
      "step  565/1000: dist 0.29 loss 11.33\n",
      "step  566/1000: dist 0.29 loss 17.64\n",
      "step  567/1000: dist 0.29 loss 32.97\n",
      "step  568/1000: dist 0.29 loss 45.17\n",
      "step  569/1000: dist 0.29 loss 35.84\n",
      "step  570/1000: dist 0.29 loss 8.59 \n",
      "step  571/1000: dist 0.29 loss 3.59 \n",
      "step  572/1000: dist 0.29 loss 20.92\n",
      "step  573/1000: dist 0.29 loss 20.77\n",
      "step  574/1000: dist 0.29 loss 3.85 \n",
      "step  575/1000: dist 0.29 loss 5.55 \n",
      "step  576/1000: dist 0.29 loss 15.39\n",
      "step  577/1000: dist 0.29 loss 7.31 \n",
      "step  578/1000: dist 0.29 loss 3.02 \n",
      "step  579/1000: dist 0.29 loss 10.18\n",
      "step  580/1000: dist 0.29 loss 7.08 \n",
      "step  581/1000: dist 0.29 loss 5.36 \n",
      "step  582/1000: dist 0.29 loss 11.98\n",
      "step  583/1000: dist 0.29 loss 11.95\n",
      "step  584/1000: dist 0.29 loss 15.34\n",
      "step  585/1000: dist 0.29 loss 22.79\n",
      "step  586/1000: dist 0.29 loss 17.95\n",
      "step  587/1000: dist 0.29 loss 10.92\n",
      "step  588/1000: dist 0.29 loss 7.59 \n",
      "step  589/1000: dist 0.29 loss 6.25 \n",
      "step  590/1000: dist 0.29 loss 14.51\n",
      "step  591/1000: dist 0.29 loss 23.03\n",
      "step  592/1000: dist 0.29 loss 23.12\n",
      "step  593/1000: dist 0.29 loss 22.27\n",
      "step  594/1000: dist 0.29 loss 17.50\n",
      "step  595/1000: dist 0.29 loss 8.61 \n",
      "step  596/1000: dist 0.29 loss 5.00 \n",
      "step  597/1000: dist 0.29 loss 7.29 \n",
      "step  598/1000: dist 0.29 loss 11.12\n",
      "step  599/1000: dist 0.29 loss 8.93 \n",
      "step  600/1000: dist 0.29 loss 2.45 \n",
      "step  601/1000: dist 0.29 loss 3.66 \n",
      "step  602/1000: dist 0.29 loss 7.76 \n",
      "step  603/1000: dist 0.28 loss 4.72 \n",
      "step  604/1000: dist 0.28 loss 1.59 \n",
      "step  605/1000: dist 0.28 loss 3.54 \n",
      "step  606/1000: dist 0.29 loss 4.59 \n",
      "step  607/1000: dist 0.28 loss 2.44 \n",
      "step  608/1000: dist 0.28 loss 1.46 \n",
      "step  609/1000: dist 0.29 loss 2.96 \n",
      "step  610/1000: dist 0.28 loss 2.76 \n",
      "step  611/1000: dist 0.28 loss 1.17 \n",
      "step  612/1000: dist 0.28 loss 1.90 \n",
      "step  613/1000: dist 0.28 loss 2.54 \n",
      "step  614/1000: dist 0.28 loss 1.72 \n",
      "step  615/1000: dist 0.28 loss 2.48 \n",
      "step  616/1000: dist 0.28 loss 4.14 \n",
      "step  617/1000: dist 0.29 loss 5.72 \n",
      "step  618/1000: dist 0.28 loss 9.74 \n",
      "step  619/1000: dist 0.28 loss 16.44\n",
      "step  620/1000: dist 0.29 loss 23.35\n",
      "step  621/1000: dist 0.28 loss 26.36\n",
      "step  622/1000: dist 0.28 loss 19.58\n",
      "step  623/1000: dist 0.28 loss 6.19 \n",
      "step  624/1000: dist 0.28 loss 0.61 \n",
      "step  625/1000: dist 0.28 loss 7.34 \n",
      "step  626/1000: dist 0.28 loss 12.92\n",
      "step  627/1000: dist 0.28 loss 7.42 \n",
      "step  628/1000: dist 0.28 loss 0.93 \n",
      "step  629/1000: dist 0.28 loss 4.01 \n",
      "step  630/1000: dist 0.28 loss 8.48 \n",
      "step  631/1000: dist 0.28 loss 5.70 \n",
      "step  632/1000: dist 0.28 loss 3.39 \n",
      "step  633/1000: dist 0.28 loss 8.37 \n",
      "step  634/1000: dist 0.28 loss 13.77\n",
      "step  635/1000: dist 0.28 loss 15.47\n",
      "step  636/1000: dist 0.28 loss 18.18\n",
      "step  637/1000: dist 0.28 loss 18.48\n",
      "step  638/1000: dist 0.28 loss 9.98 \n",
      "step  639/1000: dist 0.28 loss 1.43 \n",
      "step  640/1000: dist 0.28 loss 3.75 \n",
      "step  641/1000: dist 0.28 loss 10.17\n",
      "step  642/1000: dist 0.28 loss 10.34\n",
      "step  643/1000: dist 0.28 loss 6.58 \n",
      "step  644/1000: dist 0.28 loss 5.84 \n",
      "step  645/1000: dist 0.28 loss 9.31 \n",
      "step  646/1000: dist 0.28 loss 13.84\n",
      "step  647/1000: dist 0.28 loss 15.09\n",
      "step  648/1000: dist 0.28 loss 12.27\n",
      "step  649/1000: dist 0.28 loss 9.42 \n",
      "step  650/1000: dist 0.28 loss 8.47 \n",
      "step  651/1000: dist 0.28 loss 7.07 \n",
      "step  652/1000: dist 0.28 loss 8.12 \n",
      "step  653/1000: dist 0.28 loss 16.30\n",
      "step  654/1000: dist 0.28 loss 27.28\n",
      "step  655/1000: dist 0.28 loss 33.61\n",
      "step  656/1000: dist 0.28 loss 33.01\n",
      "step  657/1000: dist 0.28 loss 26.69\n",
      "step  658/1000: dist 0.28 loss 20.01\n",
      "step  659/1000: dist 0.28 loss 18.61\n",
      "step  660/1000: dist 0.28 loss 20.18\n",
      "step  661/1000: dist 0.28 loss 18.51\n",
      "step  662/1000: dist 0.28 loss 15.59\n",
      "step  663/1000: dist 0.28 loss 16.57\n",
      "step  664/1000: dist 0.28 loss 16.41\n",
      "step  665/1000: dist 0.28 loss 9.32 \n",
      "step  666/1000: dist 0.28 loss 3.90 \n",
      "step  667/1000: dist 0.28 loss 8.53 \n",
      "step  668/1000: dist 0.28 loss 12.98\n",
      "step  669/1000: dist 0.28 loss 7.80 \n",
      "step  670/1000: dist 0.28 loss 3.10 \n",
      "step  671/1000: dist 0.28 loss 6.64 \n",
      "step  672/1000: dist 0.28 loss 9.86 \n",
      "step  673/1000: dist 0.28 loss 8.57 \n",
      "step  674/1000: dist 0.28 loss 9.84 \n",
      "step  675/1000: dist 0.28 loss 14.81\n",
      "step  676/1000: dist 0.28 loss 18.89\n",
      "step  677/1000: dist 0.28 loss 20.58\n",
      "step  678/1000: dist 0.28 loss 17.72\n",
      "step  679/1000: dist 0.28 loss 8.93 \n",
      "step  680/1000: dist 0.28 loss 3.00 \n",
      "step  681/1000: dist 0.28 loss 4.18 \n",
      "step  682/1000: dist 0.27 loss 7.24 \n",
      "step  683/1000: dist 0.28 loss 8.75 \n",
      "step  684/1000: dist 0.27 loss 6.74 \n",
      "step  685/1000: dist 0.27 loss 2.29 \n",
      "step  686/1000: dist 0.28 loss 1.71 \n",
      "step  687/1000: dist 0.27 loss 5.19 \n",
      "step  688/1000: dist 0.27 loss 5.46 \n",
      "step  689/1000: dist 0.27 loss 2.11 \n",
      "step  690/1000: dist 0.27 loss 1.13 \n",
      "step  691/1000: dist 0.27 loss 2.81 \n",
      "step  692/1000: dist 0.28 loss 3.43 \n",
      "step  693/1000: dist 0.27 loss 2.14 \n",
      "step  694/1000: dist 0.28 loss 0.88 \n",
      "step  695/1000: dist 0.27 loss 1.39 \n",
      "step  696/1000: dist 0.27 loss 2.45 \n",
      "step  697/1000: dist 0.27 loss 1.76 \n",
      "step  698/1000: dist 0.27 loss 0.53 \n",
      "step  699/1000: dist 0.27 loss 0.99 \n",
      "step  700/1000: dist 0.27 loss 1.77 \n",
      "step  701/1000: dist 0.27 loss 1.13 \n",
      "step  702/1000: dist 0.27 loss 0.46 \n",
      "step  703/1000: dist 0.27 loss 0.87 \n",
      "step  704/1000: dist 0.27 loss 1.19 \n",
      "step  705/1000: dist 0.27 loss 0.77 \n",
      "step  706/1000: dist 0.27 loss 0.46 \n",
      "step  707/1000: dist 0.27 loss 0.65 \n",
      "step  708/1000: dist 0.27 loss 0.84 \n",
      "step  709/1000: dist 0.27 loss 0.67 \n",
      "step  710/1000: dist 0.27 loss 0.40 \n",
      "step  711/1000: dist 0.27 loss 0.47 \n",
      "step  712/1000: dist 0.27 loss 0.67 \n",
      "step  713/1000: dist 0.27 loss 0.56 \n",
      "step  714/1000: dist 0.27 loss 0.33 \n",
      "step  715/1000: dist 0.27 loss 0.40 \n",
      "step  716/1000: dist 0.27 loss 0.56 \n",
      "step  717/1000: dist 0.27 loss 0.45 \n",
      "step  718/1000: dist 0.27 loss 0.30 \n",
      "step  719/1000: dist 0.27 loss 0.38 \n",
      "step  720/1000: dist 0.27 loss 0.47 \n",
      "step  721/1000: dist 0.27 loss 0.40 \n",
      "step  722/1000: dist 0.27 loss 0.34 \n",
      "step  723/1000: dist 0.27 loss 0.40 \n",
      "step  724/1000: dist 0.27 loss 0.48 \n",
      "step  725/1000: dist 0.27 loss 0.53 \n",
      "step  726/1000: dist 0.27 loss 0.62 \n",
      "step  727/1000: dist 0.27 loss 0.89 \n",
      "step  728/1000: dist 0.27 loss 1.42 \n",
      "step  729/1000: dist 0.27 loss 2.33 \n",
      "step  730/1000: dist 0.27 loss 3.93 \n",
      "step  731/1000: dist 0.27 loss 6.68 \n",
      "step  732/1000: dist 0.27 loss 10.94\n",
      "step  733/1000: dist 0.27 loss 15.81\n",
      "step  734/1000: dist 0.27 loss 18.82\n",
      "step  735/1000: dist 0.27 loss 15.64\n",
      "step  736/1000: dist 0.27 loss 7.32 \n",
      "step  737/1000: dist 0.27 loss 1.40 \n",
      "step  738/1000: dist 0.27 loss 3.80 \n",
      "step  739/1000: dist 0.27 loss 10.37\n",
      "step  740/1000: dist 0.27 loss 13.10\n",
      "step  741/1000: dist 0.27 loss 12.50\n",
      "step  742/1000: dist 0.27 loss 16.46\n",
      "step  743/1000: dist 0.27 loss 24.98\n",
      "step  744/1000: dist 0.27 loss 25.68\n",
      "step  745/1000: dist 0.27 loss 12.94\n",
      "step  746/1000: dist 0.27 loss 1.45 \n",
      "step  747/1000: dist 0.27 loss 4.53 \n",
      "step  748/1000: dist 0.27 loss 12.64\n",
      "step  749/1000: dist 0.27 loss 11.11\n",
      "step  750/1000: dist 0.27 loss 4.38 \n",
      "step  751/1000: dist 0.27 loss 6.23 \n",
      "step  752/1000: dist 0.27 loss 14.54\n",
      "step  753/1000: dist 0.27 loss 19.38\n",
      "step  754/1000: dist 0.27 loss 24.91\n",
      "step  755/1000: dist 0.27 loss 38.32\n",
      "step  756/1000: dist 0.27 loss 49.84\n",
      "step  757/1000: dist 0.27 loss 45.00\n",
      "step  758/1000: dist 0.27 loss 26.81\n",
      "step  759/1000: dist 0.27 loss 10.55\n",
      "step  760/1000: dist 0.27 loss 12.87\n",
      "step  761/1000: dist 0.27 loss 24.01\n",
      "step  762/1000: dist 0.27 loss 19.21\n",
      "step  763/1000: dist 0.27 loss 4.68 \n",
      "step  764/1000: dist 0.27 loss 8.19 \n",
      "step  765/1000: dist 0.27 loss 18.31\n",
      "step  766/1000: dist 0.27 loss 10.53\n",
      "step  767/1000: dist 0.27 loss 4.86 \n",
      "step  768/1000: dist 0.27 loss 14.35\n",
      "step  769/1000: dist 0.27 loss 16.69\n",
      "step  770/1000: dist 0.27 loss 14.24\n",
      "step  771/1000: dist 0.27 loss 18.36\n",
      "step  772/1000: dist 0.27 loss 16.86\n",
      "step  773/1000: dist 0.27 loss 10.16\n",
      "step  774/1000: dist 0.27 loss 5.91 \n",
      "step  775/1000: dist 0.27 loss 2.40 \n",
      "step  776/1000: dist 0.27 loss 5.78 \n",
      "step  777/1000: dist 0.27 loss 9.85 \n",
      "step  778/1000: dist 0.27 loss 5.25 \n",
      "step  779/1000: dist 0.27 loss 2.71 \n",
      "step  780/1000: dist 0.27 loss 3.53 \n",
      "step  781/1000: dist 0.27 loss 3.63 \n",
      "step  782/1000: dist 0.27 loss 4.95 \n",
      "step  783/1000: dist 0.27 loss 3.32 \n",
      "step  784/1000: dist 0.27 loss 1.88 \n",
      "step  785/1000: dist 0.27 loss 3.50 \n",
      "step  786/1000: dist 0.27 loss 3.54 \n",
      "step  787/1000: dist 0.27 loss 3.26 \n",
      "step  788/1000: dist 0.27 loss 2.55 \n",
      "step  789/1000: dist 0.27 loss 2.22 \n",
      "step  790/1000: dist 0.27 loss 3.33 \n",
      "step  791/1000: dist 0.27 loss 1.91 \n",
      "step  792/1000: dist 0.27 loss 0.82 \n",
      "step  793/1000: dist 0.27 loss 1.64 \n",
      "step  794/1000: dist 0.27 loss 1.18 \n",
      "step  795/1000: dist 0.27 loss 0.74 \n",
      "step  796/1000: dist 0.27 loss 0.89 \n",
      "step  797/1000: dist 0.27 loss 1.26 \n",
      "step  798/1000: dist 0.27 loss 1.18 \n",
      "step  799/1000: dist 0.27 loss 0.55 \n",
      "step  800/1000: dist 0.27 loss 0.84 \n",
      "step  801/1000: dist 0.27 loss 0.76 \n",
      "step  802/1000: dist 0.27 loss 0.39 \n",
      "step  803/1000: dist 0.27 loss 0.65 \n",
      "step  804/1000: dist 0.27 loss 0.71 \n",
      "step  805/1000: dist 0.27 loss 0.57 \n",
      "step  806/1000: dist 0.27 loss 0.41 \n",
      "step  807/1000: dist 0.27 loss 0.51 \n",
      "step  808/1000: dist 0.27 loss 0.46 \n",
      "step  809/1000: dist 0.27 loss 0.35 \n",
      "step  810/1000: dist 0.27 loss 0.53 \n",
      "step  811/1000: dist 0.27 loss 0.39 \n",
      "step  812/1000: dist 0.27 loss 0.33 \n",
      "step  813/1000: dist 0.27 loss 0.39 \n",
      "step  814/1000: dist 0.27 loss 0.37 \n",
      "step  815/1000: dist 0.27 loss 0.36 \n",
      "step  816/1000: dist 0.27 loss 0.33 \n",
      "step  817/1000: dist 0.27 loss 0.35 \n",
      "step  818/1000: dist 0.27 loss 0.30 \n",
      "step  819/1000: dist 0.27 loss 0.34 \n",
      "step  820/1000: dist 0.27 loss 0.33 \n",
      "step  821/1000: dist 0.27 loss 0.29 \n",
      "step  822/1000: dist 0.27 loss 0.31 \n",
      "step  823/1000: dist 0.27 loss 0.31 \n",
      "step  824/1000: dist 0.27 loss 0.30 \n",
      "step  825/1000: dist 0.27 loss 0.29 \n",
      "step  826/1000: dist 0.27 loss 0.30 \n",
      "step  827/1000: dist 0.27 loss 0.28 \n",
      "step  828/1000: dist 0.27 loss 0.29 \n",
      "step  829/1000: dist 0.27 loss 0.28 \n",
      "step  830/1000: dist 0.27 loss 0.28 \n",
      "step  831/1000: dist 0.27 loss 0.29 \n",
      "step  832/1000: dist 0.27 loss 0.27 \n",
      "step  833/1000: dist 0.27 loss 0.28 \n",
      "step  834/1000: dist 0.27 loss 0.28 \n",
      "step  835/1000: dist 0.27 loss 0.28 \n",
      "step  836/1000: dist 0.27 loss 0.27 \n",
      "step  837/1000: dist 0.27 loss 0.28 \n",
      "step  838/1000: dist 0.27 loss 0.27 \n",
      "step  839/1000: dist 0.27 loss 0.27 \n",
      "step  840/1000: dist 0.27 loss 0.27 \n",
      "step  841/1000: dist 0.27 loss 0.27 \n",
      "step  842/1000: dist 0.27 loss 0.27 \n",
      "step  843/1000: dist 0.27 loss 0.27 \n",
      "step  844/1000: dist 0.27 loss 0.27 \n",
      "step  845/1000: dist 0.27 loss 0.27 \n",
      "step  846/1000: dist 0.27 loss 0.27 \n",
      "step  847/1000: dist 0.27 loss 0.27 \n",
      "step  848/1000: dist 0.27 loss 0.27 \n",
      "step  849/1000: dist 0.27 loss 0.27 \n",
      "step  850/1000: dist 0.27 loss 0.27 \n",
      "step  851/1000: dist 0.27 loss 0.27 \n",
      "step  852/1000: dist 0.27 loss 0.27 \n",
      "step  853/1000: dist 0.27 loss 0.27 \n",
      "step  854/1000: dist 0.27 loss 0.27 \n",
      "step  855/1000: dist 0.27 loss 0.27 \n",
      "step  856/1000: dist 0.27 loss 0.27 \n",
      "step  857/1000: dist 0.27 loss 0.27 \n",
      "step  858/1000: dist 0.27 loss 0.27 \n",
      "step  859/1000: dist 0.27 loss 0.27 \n",
      "step  860/1000: dist 0.27 loss 0.27 \n",
      "step  861/1000: dist 0.27 loss 0.27 \n",
      "step  862/1000: dist 0.27 loss 0.27 \n",
      "step  863/1000: dist 0.27 loss 0.27 \n",
      "step  864/1000: dist 0.27 loss 0.27 \n",
      "step  865/1000: dist 0.27 loss 0.27 \n",
      "step  866/1000: dist 0.27 loss 0.27 \n",
      "step  867/1000: dist 0.27 loss 0.27 \n",
      "step  868/1000: dist 0.27 loss 0.27 \n",
      "step  869/1000: dist 0.27 loss 0.27 \n",
      "step  870/1000: dist 0.27 loss 0.27 \n",
      "step  871/1000: dist 0.27 loss 0.27 \n",
      "step  872/1000: dist 0.27 loss 0.27 \n",
      "step  873/1000: dist 0.27 loss 0.27 \n",
      "step  874/1000: dist 0.27 loss 0.27 \n",
      "step  875/1000: dist 0.27 loss 0.27 \n",
      "step  876/1000: dist 0.27 loss 0.27 \n",
      "step  877/1000: dist 0.27 loss 0.27 \n",
      "step  878/1000: dist 0.27 loss 0.27 \n",
      "step  879/1000: dist 0.27 loss 0.27 \n",
      "step  880/1000: dist 0.27 loss 0.27 \n",
      "step  881/1000: dist 0.27 loss 0.27 \n",
      "step  882/1000: dist 0.27 loss 0.27 \n",
      "step  883/1000: dist 0.27 loss 0.27 \n",
      "step  884/1000: dist 0.27 loss 0.27 \n",
      "step  885/1000: dist 0.27 loss 0.27 \n",
      "step  886/1000: dist 0.27 loss 0.27 \n",
      "step  887/1000: dist 0.27 loss 0.27 \n",
      "step  888/1000: dist 0.27 loss 0.27 \n",
      "step  889/1000: dist 0.27 loss 0.27 \n",
      "step  890/1000: dist 0.27 loss 0.27 \n",
      "step  891/1000: dist 0.27 loss 0.27 \n",
      "step  892/1000: dist 0.27 loss 0.27 \n",
      "step  893/1000: dist 0.27 loss 0.27 \n",
      "step  894/1000: dist 0.27 loss 0.27 \n",
      "step  895/1000: dist 0.27 loss 0.27 \n",
      "step  896/1000: dist 0.27 loss 0.27 \n",
      "step  897/1000: dist 0.27 loss 0.27 \n",
      "step  898/1000: dist 0.27 loss 0.27 \n",
      "step  899/1000: dist 0.27 loss 0.27 \n",
      "step  900/1000: dist 0.27 loss 0.27 \n",
      "step  901/1000: dist 0.27 loss 0.27 \n",
      "step  902/1000: dist 0.27 loss 0.27 \n",
      "step  903/1000: dist 0.27 loss 0.27 \n",
      "step  904/1000: dist 0.27 loss 0.27 \n",
      "step  905/1000: dist 0.27 loss 0.27 \n",
      "step  906/1000: dist 0.27 loss 0.27 \n",
      "step  907/1000: dist 0.26 loss 0.26 \n",
      "step  908/1000: dist 0.26 loss 0.26 \n",
      "step  909/1000: dist 0.26 loss 0.26 \n",
      "step  910/1000: dist 0.26 loss 0.26 \n",
      "step  911/1000: dist 0.26 loss 0.26 \n",
      "step  912/1000: dist 0.26 loss 0.26 \n",
      "step  913/1000: dist 0.26 loss 0.26 \n",
      "step  914/1000: dist 0.26 loss 0.26 \n",
      "step  915/1000: dist 0.26 loss 0.26 \n",
      "step  916/1000: dist 0.26 loss 0.26 \n",
      "step  917/1000: dist 0.26 loss 0.26 \n",
      "step  918/1000: dist 0.26 loss 0.26 \n",
      "step  919/1000: dist 0.26 loss 0.26 \n",
      "step  920/1000: dist 0.26 loss 0.26 \n",
      "step  921/1000: dist 0.26 loss 0.26 \n",
      "step  922/1000: dist 0.26 loss 0.26 \n",
      "step  923/1000: dist 0.26 loss 0.26 \n",
      "step  924/1000: dist 0.26 loss 0.26 \n",
      "step  925/1000: dist 0.26 loss 0.26 \n",
      "step  926/1000: dist 0.26 loss 0.26 \n",
      "step  927/1000: dist 0.26 loss 0.26 \n",
      "step  928/1000: dist 0.26 loss 0.26 \n",
      "step  929/1000: dist 0.26 loss 0.26 \n",
      "step  930/1000: dist 0.26 loss 0.26 \n",
      "step  931/1000: dist 0.26 loss 0.26 \n",
      "step  932/1000: dist 0.26 loss 0.26 \n",
      "step  933/1000: dist 0.26 loss 0.26 \n",
      "step  934/1000: dist 0.26 loss 0.26 \n",
      "step  935/1000: dist 0.26 loss 0.26 \n",
      "step  936/1000: dist 0.26 loss 0.26 \n",
      "step  937/1000: dist 0.26 loss 0.26 \n",
      "step  938/1000: dist 0.26 loss 0.26 \n",
      "step  939/1000: dist 0.26 loss 0.26 \n",
      "step  940/1000: dist 0.26 loss 0.26 \n",
      "step  941/1000: dist 0.26 loss 0.26 \n",
      "step  942/1000: dist 0.26 loss 0.26 \n",
      "step  943/1000: dist 0.26 loss 0.26 \n",
      "step  944/1000: dist 0.26 loss 0.26 \n",
      "step  945/1000: dist 0.26 loss 0.26 \n",
      "step  946/1000: dist 0.26 loss 0.26 \n",
      "step  947/1000: dist 0.26 loss 0.26 \n",
      "step  948/1000: dist 0.26 loss 0.26 \n",
      "step  949/1000: dist 0.26 loss 0.26 \n",
      "step  950/1000: dist 0.26 loss 0.26 \n",
      "step  951/1000: dist 0.26 loss 0.26 \n",
      "step  952/1000: dist 0.26 loss 0.26 \n",
      "step  953/1000: dist 0.26 loss 0.26 \n",
      "step  954/1000: dist 0.26 loss 0.26 \n",
      "step  955/1000: dist 0.26 loss 0.26 \n",
      "step  956/1000: dist 0.26 loss 0.26 \n",
      "step  957/1000: dist 0.26 loss 0.26 \n",
      "step  958/1000: dist 0.26 loss 0.26 \n",
      "step  959/1000: dist 0.26 loss 0.26 \n",
      "step  960/1000: dist 0.26 loss 0.26 \n",
      "step  961/1000: dist 0.26 loss 0.26 \n",
      "step  962/1000: dist 0.26 loss 0.26 \n",
      "step  963/1000: dist 0.26 loss 0.26 \n",
      "step  964/1000: dist 0.26 loss 0.26 \n",
      "step  965/1000: dist 0.26 loss 0.26 \n",
      "step  966/1000: dist 0.26 loss 0.26 \n",
      "step  967/1000: dist 0.26 loss 0.26 \n",
      "step  968/1000: dist 0.26 loss 0.26 \n",
      "step  969/1000: dist 0.26 loss 0.26 \n",
      "step  970/1000: dist 0.26 loss 0.26 \n",
      "step  971/1000: dist 0.26 loss 0.26 \n",
      "step  972/1000: dist 0.26 loss 0.26 \n",
      "step  973/1000: dist 0.26 loss 0.26 \n",
      "step  974/1000: dist 0.26 loss 0.26 \n",
      "step  975/1000: dist 0.26 loss 0.26 \n",
      "step  976/1000: dist 0.26 loss 0.26 \n",
      "step  977/1000: dist 0.26 loss 0.26 \n",
      "step  978/1000: dist 0.26 loss 0.26 \n",
      "step  979/1000: dist 0.26 loss 0.26 \n",
      "step  980/1000: dist 0.26 loss 0.26 \n",
      "step  981/1000: dist 0.26 loss 0.26 \n",
      "step  982/1000: dist 0.26 loss 0.26 \n",
      "step  983/1000: dist 0.26 loss 0.26 \n",
      "step  984/1000: dist 0.26 loss 0.26 \n",
      "step  985/1000: dist 0.26 loss 0.26 \n",
      "step  986/1000: dist 0.26 loss 0.26 \n",
      "step  987/1000: dist 0.26 loss 0.26 \n",
      "step  988/1000: dist 0.26 loss 0.26 \n",
      "step  989/1000: dist 0.26 loss 0.26 \n",
      "step  990/1000: dist 0.26 loss 0.26 \n",
      "step  991/1000: dist 0.26 loss 0.26 \n",
      "step  992/1000: dist 0.26 loss 0.26 \n",
      "step  993/1000: dist 0.26 loss 0.26 \n",
      "step  994/1000: dist 0.26 loss 0.26 \n",
      "step  995/1000: dist 0.26 loss 0.26 \n",
      "step  996/1000: dist 0.26 loss 0.26 \n",
      "step  997/1000: dist 0.26 loss 0.26 \n",
      "step  998/1000: dist 0.26 loss 0.26 \n",
      "step  999/1000: dist 0.26 loss 0.26 \n",
      "step 1000/1000: dist 0.26 loss 0.26 \n",
      "Elapsed: 121.4 s\n"
     ]
    }
   ],
   "source": [
    "# HIDE OUTPUT\n",
    "cmd = f\"python /content/stylegan2-ada-pytorch/projector.py \"\\\n",
    "  f\"--save-video 0 --num-steps 1000 --outdir=out_source \"\\\n",
    "  f\"--target=cropped_source.png --network={NETWORK}\"\n",
    "!{cmd}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dBswI_gxZuIO"
   },
   "source": [
    "## Convert Target to a GAN\n",
    "\n",
    "Next, we convert the target to a GAN latent vector.  This process will also take several minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5AIpcKxDto42",
    "outputId": "8fb37c33-e1f6-401c-b6dc-e0cf843d41ca"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading networks from \"https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/ffhq.pkl\"...\n",
      "Computing W midpoint and stddev using 10000 samples...\n",
      "Setting up PyTorch plugin \"bias_act_plugin\"... Done.\n",
      "Setting up PyTorch plugin \"upfirdn2d_plugin\"... Done.\n",
      "step    1/1000: dist 0.63 loss 24568.77\n",
      "step    2/1000: dist 0.60 loss 27642.11\n",
      "step    3/1000: dist 0.60 loss 27167.12\n",
      "step    4/1000: dist 0.57 loss 26253.35\n",
      "step    5/1000: dist 0.61 loss 24959.81\n",
      "step    6/1000: dist 0.60 loss 23356.12\n",
      "step    7/1000: dist 0.56 loss 21512.13\n",
      "step    8/1000: dist 0.59 loss 19487.23\n",
      "step    9/1000: dist 0.55 loss 17341.27\n",
      "step   10/1000: dist 0.56 loss 15140.35\n",
      "step   11/1000: dist 0.63 loss 12949.49\n",
      "step   12/1000: dist 0.55 loss 10820.17\n",
      "step   13/1000: dist 0.56 loss 8802.83\n",
      "step   14/1000: dist 0.61 loss 6946.22\n",
      "step   15/1000: dist 0.58 loss 5316.71\n",
      "step   16/1000: dist 0.52 loss 3971.15\n",
      "step   17/1000: dist 0.55 loss 2941.10\n",
      "step   18/1000: dist 0.50 loss 2216.22\n",
      "step   19/1000: dist 0.51 loss 1758.78\n",
      "step   20/1000: dist 0.52 loss 1567.52\n",
      "step   21/1000: dist 0.51 loss 1602.28\n",
      "step   22/1000: dist 0.49 loss 1787.82\n",
      "step   23/1000: dist 0.48 loss 2053.34\n",
      "step   24/1000: dist 0.48 loss 2327.56\n",
      "step   25/1000: dist 0.48 loss 2538.77\n",
      "step   26/1000: dist 0.48 loss 2637.36\n",
      "step   27/1000: dist 0.49 loss 2604.07\n",
      "step   28/1000: dist 0.49 loss 2477.09\n",
      "step   29/1000: dist 0.51 loss 2317.29\n",
      "step   30/1000: dist 0.48 loss 2120.27\n",
      "step   31/1000: dist 0.47 loss 1884.58\n",
      "step   32/1000: dist 0.50 loss 1627.86\n",
      "step   33/1000: dist 0.48 loss 1388.84\n",
      "step   34/1000: dist 0.45 loss 1183.89\n",
      "step   35/1000: dist 0.45 loss 1026.39\n",
      "step   36/1000: dist 0.45 loss 909.69\n",
      "step   37/1000: dist 0.46 loss 830.82\n",
      "step   38/1000: dist 0.48 loss 805.27\n",
      "step   39/1000: dist 0.45 loss 812.57\n",
      "step   40/1000: dist 0.45 loss 834.66\n",
      "step   41/1000: dist 0.47 loss 828.71\n",
      "step   42/1000: dist 0.47 loss 761.27\n",
      "step   43/1000: dist 0.49 loss 651.15\n",
      "step   44/1000: dist 0.49 loss 521.39\n",
      "step   45/1000: dist 0.46 loss 402.71\n",
      "step   46/1000: dist 0.47 loss 318.35\n",
      "step   47/1000: dist 0.49 loss 263.81\n",
      "step   48/1000: dist 0.48 loss 241.38\n",
      "step   49/1000: dist 0.47 loss 251.26\n",
      "step   50/1000: dist 0.46 loss 304.01\n",
      "step   51/1000: dist 0.44 loss 369.49\n",
      "step   52/1000: dist 0.45 loss 401.52\n",
      "step   53/1000: dist 0.46 loss 400.59\n",
      "step   54/1000: dist 0.46 loss 369.86\n",
      "step   55/1000: dist 0.46 loss 282.55\n",
      "step   56/1000: dist 0.45 loss 201.64\n",
      "step   57/1000: dist 0.45 loss 149.67\n",
      "step   58/1000: dist 0.47 loss 80.04\n",
      "step   59/1000: dist 0.48 loss 60.75\n",
      "step   60/1000: dist 0.46 loss 60.34\n",
      "step   61/1000: dist 0.45 loss 62.42\n",
      "step   62/1000: dist 0.42 loss 95.78\n",
      "step   63/1000: dist 0.45 loss 108.14\n",
      "step   64/1000: dist 0.43 loss 133.23\n",
      "step   65/1000: dist 0.43 loss 133.46\n",
      "step   66/1000: dist 0.44 loss 115.09\n",
      "step   67/1000: dist 0.43 loss 106.48\n",
      "step   68/1000: dist 0.43 loss 71.30\n",
      "step   69/1000: dist 0.45 loss 49.85\n",
      "step   70/1000: dist 0.43 loss 29.17\n",
      "step   71/1000: dist 0.44 loss 20.93\n",
      "step   72/1000: dist 0.44 loss 18.21\n",
      "step   73/1000: dist 0.42 loss 20.99\n",
      "step   74/1000: dist 0.43 loss 30.88\n",
      "step   75/1000: dist 0.45 loss 32.53\n",
      "step   76/1000: dist 0.45 loss 40.11\n",
      "step   77/1000: dist 0.45 loss 37.00\n",
      "step   78/1000: dist 0.44 loss 32.15\n",
      "step   79/1000: dist 0.41 loss 30.82\n",
      "step   80/1000: dist 0.42 loss 27.17\n",
      "step   81/1000: dist 0.41 loss 22.75\n",
      "step   82/1000: dist 0.42 loss 13.63\n",
      "step   83/1000: dist 0.42 loss 13.14\n",
      "step   84/1000: dist 0.41 loss 15.89\n",
      "step   85/1000: dist 0.40 loss 15.54\n",
      "step   86/1000: dist 0.42 loss 12.85\n",
      "step   87/1000: dist 0.42 loss 10.69\n",
      "step   88/1000: dist 0.44 loss 11.77\n",
      "step   89/1000: dist 0.41 loss 10.23\n",
      "step   90/1000: dist 0.41 loss 7.86 \n",
      "step   91/1000: dist 0.42 loss 6.77 \n",
      "step   92/1000: dist 0.41 loss 6.25 \n",
      "step   93/1000: dist 0.41 loss 7.11 \n",
      "step   94/1000: dist 0.41 loss 8.53 \n",
      "step   95/1000: dist 0.40 loss 10.37\n",
      "step   96/1000: dist 0.41 loss 11.90\n",
      "step   97/1000: dist 0.41 loss 11.11\n",
      "step   98/1000: dist 0.41 loss 7.58 \n",
      "step   99/1000: dist 0.41 loss 3.91 \n",
      "step  100/1000: dist 0.40 loss 3.10 \n",
      "step  101/1000: dist 0.40 loss 4.27 \n",
      "step  102/1000: dist 0.40 loss 4.44 \n",
      "step  103/1000: dist 0.41 loss 2.91 \n",
      "step  104/1000: dist 0.44 loss 2.21 \n",
      "step  105/1000: dist 0.40 loss 3.64 \n",
      "step  106/1000: dist 0.42 loss 5.15 \n",
      "step  107/1000: dist 0.42 loss 5.45 \n",
      "step  108/1000: dist 0.41 loss 5.54 \n",
      "step  109/1000: dist 0.42 loss 5.72 \n",
      "step  110/1000: dist 0.40 loss 5.34 \n",
      "step  111/1000: dist 0.40 loss 4.88 \n",
      "step  112/1000: dist 0.39 loss 6.34 \n",
      "step  113/1000: dist 0.40 loss 10.53\n",
      "step  114/1000: dist 0.41 loss 14.98\n",
      "step  115/1000: dist 0.41 loss 14.98\n",
      "step  116/1000: dist 0.42 loss 9.25 \n",
      "step  117/1000: dist 0.40 loss 5.78 \n",
      "step  118/1000: dist 0.42 loss 9.34 \n",
      "step  119/1000: dist 0.41 loss 12.45\n",
      "step  120/1000: dist 0.42 loss 10.44\n",
      "step  121/1000: dist 0.41 loss 11.29\n",
      "step  122/1000: dist 0.41 loss 16.97\n",
      "step  123/1000: dist 0.41 loss 13.82\n",
      "step  124/1000: dist 0.40 loss 3.49 \n",
      "step  125/1000: dist 0.40 loss 4.26 \n",
      "step  126/1000: dist 0.40 loss 12.04\n",
      "step  127/1000: dist 0.40 loss 9.42 \n",
      "step  128/1000: dist 0.39 loss 2.48 \n",
      "step  129/1000: dist 0.42 loss 5.23 \n",
      "step  130/1000: dist 0.40 loss 8.20 \n",
      "step  131/1000: dist 0.42 loss 3.68 \n",
      "step  132/1000: dist 0.40 loss 2.79 \n",
      "step  133/1000: dist 0.39 loss 6.47 \n",
      "step  134/1000: dist 0.39 loss 5.09 \n",
      "step  135/1000: dist 0.42 loss 3.70 \n",
      "step  136/1000: dist 0.39 loss 8.50 \n",
      "step  137/1000: dist 0.39 loss 13.20\n",
      "step  138/1000: dist 0.39 loss 15.67\n",
      "step  139/1000: dist 0.39 loss 15.73\n",
      "step  140/1000: dist 0.39 loss 10.51\n",
      "step  141/1000: dist 0.39 loss 8.84 \n",
      "step  142/1000: dist 0.39 loss 15.89\n",
      "step  143/1000: dist 0.40 loss 17.21\n",
      "step  144/1000: dist 0.38 loss 8.13 \n",
      "step  145/1000: dist 0.40 loss 7.21 \n",
      "step  146/1000: dist 0.39 loss 15.88\n",
      "step  147/1000: dist 0.41 loss 16.82\n",
      "step  148/1000: dist 0.40 loss 10.13\n",
      "step  149/1000: dist 0.39 loss 6.30 \n",
      "step  150/1000: dist 0.39 loss 4.91 \n",
      "step  151/1000: dist 0.40 loss 5.57 \n",
      "step  152/1000: dist 0.40 loss 9.53 \n",
      "step  153/1000: dist 0.39 loss 9.50 \n",
      "step  154/1000: dist 0.39 loss 5.56 \n",
      "step  155/1000: dist 0.38 loss 8.20 \n",
      "step  156/1000: dist 0.39 loss 14.62\n",
      "step  157/1000: dist 0.39 loss 13.69\n",
      "step  158/1000: dist 0.39 loss 7.50 \n",
      "step  159/1000: dist 0.38 loss 4.26 \n",
      "step  160/1000: dist 0.40 loss 5.56 \n",
      "step  161/1000: dist 0.39 loss 9.38 \n",
      "step  162/1000: dist 0.40 loss 13.38\n",
      "step  163/1000: dist 0.42 loss 16.43\n",
      "step  164/1000: dist 0.39 loss 22.84\n",
      "step  165/1000: dist 0.39 loss 35.32\n",
      "step  166/1000: dist 0.38 loss 38.83\n",
      "step  167/1000: dist 0.38 loss 17.69\n",
      "step  168/1000: dist 0.40 loss 7.40 \n",
      "step  169/1000: dist 0.40 loss 23.03\n",
      "step  170/1000: dist 0.41 loss 17.91\n",
      "step  171/1000: dist 0.40 loss 3.20 \n",
      "step  172/1000: dist 0.40 loss 13.44\n",
      "step  173/1000: dist 0.40 loss 13.49\n",
      "step  174/1000: dist 0.39 loss 7.86 \n",
      "step  175/1000: dist 0.39 loss 14.67\n",
      "step  176/1000: dist 0.39 loss 9.40 \n",
      "step  177/1000: dist 0.39 loss 10.84\n",
      "step  178/1000: dist 0.38 loss 16.66\n",
      "step  179/1000: dist 0.39 loss 8.86 \n",
      "step  180/1000: dist 0.38 loss 8.32 \n",
      "step  181/1000: dist 0.39 loss 6.36 \n",
      "step  182/1000: dist 0.39 loss 5.12 \n",
      "step  183/1000: dist 0.39 loss 10.92\n",
      "step  184/1000: dist 0.39 loss 10.32\n",
      "step  185/1000: dist 0.39 loss 13.67\n",
      "step  186/1000: dist 0.39 loss 15.94\n",
      "step  187/1000: dist 0.39 loss 13.11\n",
      "step  188/1000: dist 0.39 loss 11.61\n",
      "step  189/1000: dist 0.39 loss 8.15 \n",
      "step  190/1000: dist 0.38 loss 10.88\n",
      "step  191/1000: dist 0.40 loss 13.93\n",
      "step  192/1000: dist 0.38 loss 11.13\n",
      "step  193/1000: dist 0.37 loss 10.81\n",
      "step  194/1000: dist 0.37 loss 15.03\n",
      "step  195/1000: dist 0.38 loss 25.86\n",
      "step  196/1000: dist 0.39 loss 37.01\n",
      "step  197/1000: dist 0.38 loss 37.96\n",
      "step  198/1000: dist 0.39 loss 21.87\n",
      "step  199/1000: dist 0.38 loss 7.17 \n",
      "step  200/1000: dist 0.39 loss 14.34\n",
      "step  201/1000: dist 0.38 loss 19.18\n",
      "step  202/1000: dist 0.38 loss 9.69 \n",
      "step  203/1000: dist 0.38 loss 10.58\n",
      "step  204/1000: dist 0.38 loss 12.80\n",
      "step  205/1000: dist 0.38 loss 4.86 \n",
      "step  206/1000: dist 0.38 loss 7.54 \n",
      "step  207/1000: dist 0.37 loss 11.50\n",
      "step  208/1000: dist 0.38 loss 3.47 \n",
      "step  209/1000: dist 0.37 loss 4.03 \n",
      "step  210/1000: dist 0.37 loss 8.23 \n",
      "step  211/1000: dist 0.37 loss 3.73 \n",
      "step  212/1000: dist 0.37 loss 3.60 \n",
      "step  213/1000: dist 0.37 loss 4.48 \n",
      "step  214/1000: dist 0.37 loss 2.89 \n",
      "step  215/1000: dist 0.38 loss 4.53 \n",
      "step  216/1000: dist 0.37 loss 2.58 \n",
      "step  217/1000: dist 0.37 loss 1.50 \n",
      "step  218/1000: dist 0.37 loss 4.20 \n",
      "step  219/1000: dist 0.38 loss 2.48 \n",
      "step  220/1000: dist 0.38 loss 1.55 \n",
      "step  221/1000: dist 0.37 loss 2.85 \n",
      "step  222/1000: dist 0.38 loss 2.44 \n",
      "step  223/1000: dist 0.37 loss 3.21 \n",
      "step  224/1000: dist 0.38 loss 3.23 \n",
      "step  225/1000: dist 0.38 loss 3.19 \n",
      "step  226/1000: dist 0.38 loss 5.29 \n",
      "step  227/1000: dist 0.37 loss 5.61 \n",
      "step  228/1000: dist 0.38 loss 5.14 \n",
      "step  229/1000: dist 0.38 loss 4.79 \n",
      "step  230/1000: dist 0.37 loss 2.85 \n",
      "step  231/1000: dist 0.37 loss 1.50 \n",
      "step  232/1000: dist 0.37 loss 1.02 \n",
      "step  233/1000: dist 0.38 loss 1.11 \n",
      "step  234/1000: dist 0.37 loss 2.43 \n",
      "step  235/1000: dist 0.38 loss 2.87 \n",
      "step  236/1000: dist 0.37 loss 2.11 \n",
      "step  237/1000: dist 0.37 loss 1.41 \n",
      "step  238/1000: dist 0.37 loss 0.73 \n",
      "step  239/1000: dist 0.37 loss 0.76 \n",
      "step  240/1000: dist 0.36 loss 1.32 \n",
      "step  241/1000: dist 0.37 loss 1.43 \n",
      "step  242/1000: dist 0.37 loss 1.41 \n",
      "step  243/1000: dist 0.37 loss 1.16 \n",
      "step  244/1000: dist 0.36 loss 0.65 \n",
      "step  245/1000: dist 0.36 loss 0.58 \n",
      "step  246/1000: dist 0.37 loss 0.78 \n",
      "step  247/1000: dist 0.37 loss 1.00 \n",
      "step  248/1000: dist 0.38 loss 1.29 \n",
      "step  249/1000: dist 0.38 loss 1.37 \n",
      "step  250/1000: dist 0.39 loss 1.63 \n",
      "step  251/1000: dist 0.36 loss 2.78 \n",
      "step  252/1000: dist 0.37 loss 5.55 \n",
      "step  253/1000: dist 0.37 loss 10.95\n",
      "step  254/1000: dist 0.36 loss 18.49\n",
      "step  255/1000: dist 0.36 loss 21.99\n",
      "step  256/1000: dist 0.36 loss 13.80\n",
      "step  257/1000: dist 0.37 loss 3.10 \n",
      "step  258/1000: dist 0.37 loss 6.43 \n",
      "step  259/1000: dist 0.36 loss 16.95\n",
      "step  260/1000: dist 0.37 loss 18.68\n",
      "step  261/1000: dist 0.36 loss 19.48\n",
      "step  262/1000: dist 0.35 loss 31.48\n",
      "step  263/1000: dist 0.38 loss 37.36\n",
      "step  264/1000: dist 0.36 loss 25.85\n",
      "step  265/1000: dist 0.36 loss 16.00\n",
      "step  266/1000: dist 0.36 loss 17.50\n",
      "step  267/1000: dist 0.36 loss 19.14\n",
      "step  268/1000: dist 0.37 loss 16.35\n",
      "step  269/1000: dist 0.36 loss 10.63\n",
      "step  270/1000: dist 0.35 loss 5.18 \n",
      "step  271/1000: dist 0.36 loss 8.53 \n",
      "step  272/1000: dist 0.36 loss 13.82\n",
      "step  273/1000: dist 0.36 loss 8.40 \n",
      "step  274/1000: dist 0.35 loss 3.64 \n",
      "step  275/1000: dist 0.37 loss 8.15 \n",
      "step  276/1000: dist 0.36 loss 9.72 \n",
      "step  277/1000: dist 0.37 loss 8.79 \n",
      "step  278/1000: dist 0.36 loss 14.53\n",
      "step  279/1000: dist 0.35 loss 19.90\n",
      "step  280/1000: dist 0.35 loss 18.01\n",
      "step  281/1000: dist 0.36 loss 12.53\n",
      "step  282/1000: dist 0.36 loss 7.74 \n",
      "step  283/1000: dist 0.36 loss 7.64 \n",
      "step  284/1000: dist 0.35 loss 14.28\n",
      "step  285/1000: dist 0.36 loss 22.87\n",
      "step  286/1000: dist 0.35 loss 30.05\n",
      "step  287/1000: dist 0.35 loss 42.14\n",
      "step  288/1000: dist 0.36 loss 57.32\n",
      "step  289/1000: dist 0.37 loss 58.00\n",
      "step  290/1000: dist 0.37 loss 40.22\n",
      "step  291/1000: dist 0.36 loss 29.92\n",
      "step  292/1000: dist 0.36 loss 37.92\n",
      "step  293/1000: dist 0.36 loss 39.55\n",
      "step  294/1000: dist 0.35 loss 24.88\n",
      "step  295/1000: dist 0.35 loss 19.24\n",
      "step  296/1000: dist 0.36 loss 29.04\n",
      "step  297/1000: dist 0.35 loss 28.44\n",
      "step  298/1000: dist 0.35 loss 14.75\n",
      "step  299/1000: dist 0.36 loss 13.28\n",
      "step  300/1000: dist 0.35 loss 23.15\n",
      "step  301/1000: dist 0.36 loss 21.66\n",
      "step  302/1000: dist 0.36 loss 11.28\n",
      "step  303/1000: dist 0.36 loss 8.81 \n",
      "step  304/1000: dist 0.36 loss 10.64\n",
      "step  305/1000: dist 0.37 loss 8.16 \n",
      "step  306/1000: dist 0.35 loss 7.31 \n",
      "step  307/1000: dist 0.36 loss 10.09\n",
      "step  308/1000: dist 0.35 loss 8.90 \n",
      "step  309/1000: dist 0.35 loss 4.98 \n",
      "step  310/1000: dist 0.35 loss 4.78 \n",
      "step  311/1000: dist 0.35 loss 6.37 \n",
      "step  312/1000: dist 0.35 loss 6.58 \n",
      "step  313/1000: dist 0.35 loss 7.24 \n",
      "step  314/1000: dist 0.35 loss 9.44 \n",
      "step  315/1000: dist 0.35 loss 13.21\n",
      "step  316/1000: dist 0.35 loss 18.81\n",
      "step  317/1000: dist 0.35 loss 21.85\n",
      "step  318/1000: dist 0.35 loss 18.14\n",
      "step  319/1000: dist 0.35 loss 11.98\n",
      "step  320/1000: dist 0.35 loss 11.39\n",
      "step  321/1000: dist 0.36 loss 14.91\n",
      "step  322/1000: dist 0.35 loss 15.84\n",
      "step  323/1000: dist 0.36 loss 11.16\n",
      "step  324/1000: dist 0.35 loss 5.78 \n",
      "step  325/1000: dist 0.35 loss 6.52 \n",
      "step  326/1000: dist 0.36 loss 9.82 \n",
      "step  327/1000: dist 0.35 loss 8.05 \n",
      "step  328/1000: dist 0.35 loss 3.55 \n",
      "step  329/1000: dist 0.36 loss 3.58 \n",
      "step  330/1000: dist 0.35 loss 6.34 \n",
      "step  331/1000: dist 0.34 loss 5.66 \n",
      "step  332/1000: dist 0.35 loss 2.97 \n",
      "step  333/1000: dist 0.35 loss 2.66 \n",
      "step  334/1000: dist 0.35 loss 3.64 \n",
      "step  335/1000: dist 0.35 loss 3.52 \n",
      "step  336/1000: dist 0.35 loss 3.05 \n",
      "step  337/1000: dist 0.35 loss 2.88 \n",
      "step  338/1000: dist 0.35 loss 2.95 \n",
      "step  339/1000: dist 0.35 loss 4.19 \n",
      "step  340/1000: dist 0.34 loss 6.59 \n",
      "step  341/1000: dist 0.35 loss 9.43 \n",
      "step  342/1000: dist 0.35 loss 13.87\n",
      "step  343/1000: dist 0.34 loss 20.12\n",
      "step  344/1000: dist 0.35 loss 23.36\n",
      "step  345/1000: dist 0.34 loss 20.32\n",
      "step  346/1000: dist 0.35 loss 16.37\n",
      "step  347/1000: dist 0.35 loss 16.01\n",
      "step  348/1000: dist 0.34 loss 13.92\n",
      "step  349/1000: dist 0.34 loss 8.05 \n",
      "step  350/1000: dist 0.34 loss 4.54 \n",
      "step  351/1000: dist 0.34 loss 7.58 \n",
      "step  352/1000: dist 0.34 loss 10.71\n",
      "step  353/1000: dist 0.35 loss 7.02 \n",
      "step  354/1000: dist 0.34 loss 2.61 \n",
      "step  355/1000: dist 0.34 loss 5.11 \n",
      "step  356/1000: dist 0.34 loss 9.35 \n",
      "step  357/1000: dist 0.34 loss 8.74 \n",
      "step  358/1000: dist 0.34 loss 9.35 \n",
      "step  359/1000: dist 0.34 loss 17.84\n",
      "step  360/1000: dist 0.34 loss 25.91\n",
      "step  361/1000: dist 0.34 loss 22.36\n",
      "step  362/1000: dist 0.34 loss 9.73 \n",
      "step  363/1000: dist 0.34 loss 3.08 \n",
      "step  364/1000: dist 0.34 loss 7.06 \n",
      "step  365/1000: dist 0.34 loss 11.71\n",
      "step  366/1000: dist 0.33 loss 9.02 \n",
      "step  367/1000: dist 0.34 loss 3.32 \n",
      "step  368/1000: dist 0.34 loss 3.70 \n",
      "step  369/1000: dist 0.34 loss 7.23 \n",
      "step  370/1000: dist 0.34 loss 5.62 \n",
      "step  371/1000: dist 0.34 loss 2.02 \n",
      "step  372/1000: dist 0.34 loss 3.21 \n",
      "step  373/1000: dist 0.33 loss 4.99 \n",
      "step  374/1000: dist 0.34 loss 2.75 \n",
      "step  375/1000: dist 0.34 loss 1.43 \n",
      "step  376/1000: dist 0.33 loss 3.18 \n",
      "step  377/1000: dist 0.34 loss 3.04 \n",
      "step  378/1000: dist 0.33 loss 1.30 \n",
      "step  379/1000: dist 0.34 loss 2.00 \n",
      "step  380/1000: dist 0.34 loss 3.04 \n",
      "step  381/1000: dist 0.34 loss 2.39 \n",
      "step  382/1000: dist 0.34 loss 3.30 \n",
      "step  383/1000: dist 0.33 loss 6.57 \n",
      "step  384/1000: dist 0.34 loss 10.44\n",
      "step  385/1000: dist 0.35 loss 16.30\n",
      "step  386/1000: dist 0.35 loss 22.44\n",
      "step  387/1000: dist 0.34 loss 20.03\n",
      "step  388/1000: dist 0.34 loss 7.82 \n",
      "step  389/1000: dist 0.34 loss 0.80 \n",
      "step  390/1000: dist 0.34 loss 5.98 \n",
      "step  391/1000: dist 0.34 loss 11.64\n",
      "step  392/1000: dist 0.35 loss 7.74 \n",
      "step  393/1000: dist 0.34 loss 1.41 \n",
      "step  394/1000: dist 0.33 loss 3.10 \n",
      "step  395/1000: dist 0.33 loss 7.24 \n",
      "step  396/1000: dist 0.34 loss 4.74 \n",
      "step  397/1000: dist 0.34 loss 0.86 \n",
      "step  398/1000: dist 0.34 loss 2.83 \n",
      "step  399/1000: dist 0.33 loss 4.92 \n",
      "step  400/1000: dist 0.34 loss 2.22 \n",
      "step  401/1000: dist 0.34 loss 0.73 \n",
      "step  402/1000: dist 0.34 loss 2.93 \n",
      "step  403/1000: dist 0.35 loss 3.00 \n",
      "step  404/1000: dist 0.35 loss 0.81 \n",
      "step  405/1000: dist 0.33 loss 1.24 \n",
      "step  406/1000: dist 0.33 loss 2.59 \n",
      "step  407/1000: dist 0.33 loss 1.49 \n",
      "step  408/1000: dist 0.34 loss 0.74 \n",
      "step  409/1000: dist 0.34 loss 2.00 \n",
      "step  410/1000: dist 0.34 loss 2.39 \n",
      "step  411/1000: dist 0.34 loss 1.92 \n",
      "step  412/1000: dist 0.33 loss 3.25 \n",
      "step  413/1000: dist 0.34 loss 5.71 \n",
      "step  414/1000: dist 0.34 loss 7.95 \n",
      "step  415/1000: dist 0.34 loss 11.13\n",
      "step  416/1000: dist 0.34 loss 14.47\n",
      "step  417/1000: dist 0.33 loss 13.91\n",
      "step  418/1000: dist 0.33 loss 9.14 \n",
      "step  419/1000: dist 0.33 loss 5.72 \n",
      "step  420/1000: dist 0.33 loss 7.88 \n",
      "step  421/1000: dist 0.33 loss 13.35\n",
      "step  422/1000: dist 0.34 loss 15.98\n",
      "step  423/1000: dist 0.34 loss 11.85\n",
      "step  424/1000: dist 0.34 loss 4.34 \n",
      "step  425/1000: dist 0.34 loss 1.30 \n",
      "step  426/1000: dist 0.33 loss 4.18 \n",
      "step  427/1000: dist 0.33 loss 7.01 \n",
      "step  428/1000: dist 0.33 loss 5.81 \n",
      "step  429/1000: dist 0.35 loss 3.10 \n",
      "step  430/1000: dist 0.33 loss 2.29 \n",
      "step  431/1000: dist 0.33 loss 3.03 \n",
      "step  432/1000: dist 0.33 loss 3.42 \n",
      "step  433/1000: dist 0.33 loss 3.30 \n",
      "step  434/1000: dist 0.33 loss 3.13 \n",
      "step  435/1000: dist 0.33 loss 3.17 \n",
      "step  436/1000: dist 0.33 loss 3.97 \n",
      "step  437/1000: dist 0.33 loss 6.23 \n",
      "step  438/1000: dist 0.33 loss 9.71 \n",
      "step  439/1000: dist 0.33 loss 13.88\n",
      "step  440/1000: dist 0.33 loss 18.35\n",
      "step  441/1000: dist 0.33 loss 20.96\n",
      "step  442/1000: dist 0.33 loss 18.03\n",
      "step  443/1000: dist 0.33 loss 10.45\n",
      "step  444/1000: dist 0.33 loss 4.76 \n",
      "step  445/1000: dist 0.34 loss 5.05 \n",
      "step  446/1000: dist 0.33 loss 7.73 \n",
      "step  447/1000: dist 0.33 loss 7.25 \n",
      "step  448/1000: dist 0.32 loss 4.44 \n",
      "step  449/1000: dist 0.33 loss 4.04 \n",
      "step  450/1000: dist 0.32 loss 5.65 \n",
      "step  451/1000: dist 0.33 loss 5.03 \n",
      "step  452/1000: dist 0.33 loss 2.42 \n",
      "step  453/1000: dist 0.32 loss 2.29 \n",
      "step  454/1000: dist 0.33 loss 5.08 \n",
      "step  455/1000: dist 0.32 loss 6.55 \n",
      "step  456/1000: dist 0.32 loss 6.01 \n",
      "step  457/1000: dist 0.33 loss 7.84 \n",
      "step  458/1000: dist 0.32 loss 13.89\n",
      "step  459/1000: dist 0.32 loss 19.44\n",
      "step  460/1000: dist 0.32 loss 18.82\n",
      "step  461/1000: dist 0.32 loss 11.18\n",
      "step  462/1000: dist 0.33 loss 3.96 \n",
      "step  463/1000: dist 0.32 loss 4.37 \n",
      "step  464/1000: dist 0.32 loss 10.30\n",
      "step  465/1000: dist 0.32 loss 13.48\n",
      "step  466/1000: dist 0.32 loss 10.60\n",
      "step  467/1000: dist 0.32 loss 8.22 \n",
      "step  468/1000: dist 0.32 loss 10.44\n",
      "step  469/1000: dist 0.32 loss 11.50\n",
      "step  470/1000: dist 0.32 loss 6.87 \n",
      "step  471/1000: dist 0.33 loss 2.77 \n",
      "step  472/1000: dist 0.32 loss 5.52 \n",
      "step  473/1000: dist 0.32 loss 11.72\n",
      "step  474/1000: dist 0.32 loss 17.15\n",
      "step  475/1000: dist 0.32 loss 23.26\n",
      "step  476/1000: dist 0.32 loss 27.49\n",
      "step  477/1000: dist 0.32 loss 19.85\n",
      "step  478/1000: dist 0.32 loss 5.23 \n",
      "step  479/1000: dist 0.33 loss 2.14 \n",
      "step  480/1000: dist 0.32 loss 11.52\n",
      "step  481/1000: dist 0.32 loss 14.64\n",
      "step  482/1000: dist 0.32 loss 5.63 \n",
      "step  483/1000: dist 0.32 loss 1.35 \n",
      "step  484/1000: dist 0.32 loss 7.80 \n",
      "step  485/1000: dist 0.32 loss 10.81\n",
      "step  486/1000: dist 0.33 loss 7.70 \n",
      "step  487/1000: dist 0.33 loss 11.75\n",
      "step  488/1000: dist 0.32 loss 23.55\n",
      "step  489/1000: dist 0.32 loss 30.50\n",
      "step  490/1000: dist 0.32 loss 26.71\n",
      "step  491/1000: dist 0.33 loss 14.44\n",
      "step  492/1000: dist 0.32 loss 4.90 \n",
      "step  493/1000: dist 0.32 loss 9.22 \n",
      "step  494/1000: dist 0.32 loss 17.97\n",
      "step  495/1000: dist 0.32 loss 15.02\n",
      "step  496/1000: dist 0.32 loss 12.14\n",
      "step  497/1000: dist 0.32 loss 25.29\n",
      "step  498/1000: dist 0.31 loss 37.94\n",
      "step  499/1000: dist 0.31 loss 37.77\n",
      "step  500/1000: dist 0.32 loss 34.20\n",
      "step  501/1000: dist 0.32 loss 22.55\n",
      "step  502/1000: dist 0.32 loss 8.23 \n",
      "step  503/1000: dist 0.32 loss 17.44\n",
      "step  504/1000: dist 0.32 loss 37.55\n",
      "step  505/1000: dist 0.31 loss 39.15\n",
      "step  506/1000: dist 0.32 loss 38.22\n",
      "step  507/1000: dist 0.32 loss 38.50\n",
      "step  508/1000: dist 0.32 loss 19.56\n",
      "step  509/1000: dist 0.32 loss 7.97 \n",
      "step  510/1000: dist 0.32 loss 22.48\n",
      "step  511/1000: dist 0.32 loss 23.17\n",
      "step  512/1000: dist 0.32 loss 7.87 \n",
      "step  513/1000: dist 0.32 loss 15.68\n",
      "step  514/1000: dist 0.32 loss 23.92\n",
      "step  515/1000: dist 0.32 loss 15.09\n",
      "step  516/1000: dist 0.32 loss 22.75\n",
      "step  517/1000: dist 0.32 loss 31.83\n",
      "step  518/1000: dist 0.31 loss 22.17\n",
      "step  519/1000: dist 0.31 loss 22.18\n",
      "step  520/1000: dist 0.31 loss 26.55\n",
      "step  521/1000: dist 0.31 loss 22.81\n",
      "step  522/1000: dist 0.32 loss 24.71\n",
      "step  523/1000: dist 0.31 loss 23.00\n",
      "step  524/1000: dist 0.31 loss 21.71\n",
      "step  525/1000: dist 0.31 loss 29.47\n",
      "step  526/1000: dist 0.31 loss 26.77\n",
      "step  527/1000: dist 0.31 loss 14.91\n",
      "step  528/1000: dist 0.32 loss 8.91 \n",
      "step  529/1000: dist 0.32 loss 13.27\n",
      "step  530/1000: dist 0.31 loss 26.22\n",
      "step  531/1000: dist 0.31 loss 31.21\n",
      "step  532/1000: dist 0.31 loss 27.09\n",
      "step  533/1000: dist 0.31 loss 23.98\n",
      "step  534/1000: dist 0.31 loss 17.37\n",
      "step  535/1000: dist 0.31 loss 11.66\n",
      "step  536/1000: dist 0.31 loss 14.19\n",
      "step  537/1000: dist 0.31 loss 23.17\n",
      "step  538/1000: dist 0.31 loss 32.38\n",
      "step  539/1000: dist 0.31 loss 37.40\n",
      "step  540/1000: dist 0.31 loss 39.18\n",
      "step  541/1000: dist 0.31 loss 27.70\n",
      "step  542/1000: dist 0.31 loss 10.29\n",
      "step  543/1000: dist 0.31 loss 15.83\n",
      "step  544/1000: dist 0.31 loss 30.35\n",
      "step  545/1000: dist 0.31 loss 24.29\n",
      "step  546/1000: dist 0.31 loss 14.30\n",
      "step  547/1000: dist 0.32 loss 20.68\n",
      "step  548/1000: dist 0.31 loss 19.18\n",
      "step  549/1000: dist 0.31 loss 4.18 \n",
      "step  550/1000: dist 0.31 loss 5.86 \n",
      "step  551/1000: dist 0.32 loss 13.53\n",
      "step  552/1000: dist 0.31 loss 7.49 \n",
      "step  553/1000: dist 0.31 loss 7.37 \n",
      "step  554/1000: dist 0.31 loss 10.44\n",
      "step  555/1000: dist 0.31 loss 3.34 \n",
      "step  556/1000: dist 0.32 loss 3.55 \n",
      "step  557/1000: dist 0.31 loss 9.78 \n",
      "step  558/1000: dist 0.32 loss 7.77 \n",
      "step  559/1000: dist 0.32 loss 8.57 \n",
      "step  560/1000: dist 0.31 loss 14.80\n",
      "step  561/1000: dist 0.31 loss 18.29\n",
      "step  562/1000: dist 0.31 loss 22.51\n",
      "step  563/1000: dist 0.32 loss 21.73\n",
      "step  564/1000: dist 0.32 loss 9.16 \n",
      "step  565/1000: dist 0.31 loss 1.69 \n",
      "step  566/1000: dist 0.31 loss 6.20 \n",
      "step  567/1000: dist 0.31 loss 11.43\n",
      "step  568/1000: dist 0.32 loss 11.19\n",
      "step  569/1000: dist 0.31 loss 6.65 \n",
      "step  570/1000: dist 0.31 loss 7.06 \n",
      "step  571/1000: dist 0.31 loss 15.96\n",
      "step  572/1000: dist 0.31 loss 21.67\n",
      "step  573/1000: dist 0.32 loss 20.10\n",
      "step  574/1000: dist 0.32 loss 17.21\n",
      "step  575/1000: dist 0.31 loss 11.33\n",
      "step  576/1000: dist 0.31 loss 4.11 \n",
      "step  577/1000: dist 0.32 loss 4.67 \n",
      "step  578/1000: dist 0.31 loss 11.42\n",
      "step  579/1000: dist 0.32 loss 12.86\n",
      "step  580/1000: dist 0.33 loss 7.76 \n",
      "step  581/1000: dist 0.32 loss 7.98 \n",
      "step  582/1000: dist 0.32 loss 15.19\n",
      "step  583/1000: dist 0.32 loss 16.73\n",
      "step  584/1000: dist 0.32 loss 9.93 \n",
      "step  585/1000: dist 0.32 loss 5.47 \n",
      "step  586/1000: dist 0.32 loss 5.21 \n",
      "step  587/1000: dist 0.32 loss 3.95 \n",
      "step  588/1000: dist 0.31 loss 3.71 \n",
      "step  589/1000: dist 0.31 loss 6.76 \n",
      "step  590/1000: dist 0.31 loss 7.78 \n",
      "step  591/1000: dist 0.31 loss 4.75 \n",
      "step  592/1000: dist 0.31 loss 4.03 \n",
      "step  593/1000: dist 0.31 loss 8.56 \n",
      "step  594/1000: dist 0.31 loss 13.80\n",
      "step  595/1000: dist 0.31 loss 16.86\n",
      "step  596/1000: dist 0.31 loss 18.13\n",
      "step  597/1000: dist 0.30 loss 14.87\n",
      "step  598/1000: dist 0.31 loss 7.32 \n",
      "step  599/1000: dist 0.31 loss 2.98 \n",
      "step  600/1000: dist 0.31 loss 5.80 \n",
      "step  601/1000: dist 0.31 loss 10.04\n",
      "step  602/1000: dist 0.31 loss 10.01\n",
      "step  603/1000: dist 0.31 loss 7.76 \n",
      "step  604/1000: dist 0.31 loss 9.13 \n",
      "step  605/1000: dist 0.31 loss 14.98\n",
      "step  606/1000: dist 0.30 loss 19.76\n",
      "step  607/1000: dist 0.31 loss 18.18\n",
      "step  608/1000: dist 0.31 loss 11.99\n",
      "step  609/1000: dist 0.30 loss 6.24 \n",
      "step  610/1000: dist 0.30 loss 3.85 \n",
      "step  611/1000: dist 0.30 loss 4.49 \n",
      "step  612/1000: dist 0.30 loss 7.00 \n",
      "step  613/1000: dist 0.31 loss 8.26 \n",
      "step  614/1000: dist 0.30 loss 5.26 \n",
      "step  615/1000: dist 0.30 loss 1.53 \n",
      "step  616/1000: dist 0.30 loss 2.46 \n",
      "step  617/1000: dist 0.30 loss 5.71 \n",
      "step  618/1000: dist 0.30 loss 5.16 \n",
      "step  619/1000: dist 0.30 loss 1.92 \n",
      "step  620/1000: dist 0.30 loss 1.88 \n",
      "step  621/1000: dist 0.30 loss 4.64 \n",
      "step  622/1000: dist 0.30 loss 5.29 \n",
      "step  623/1000: dist 0.30 loss 4.01 \n",
      "step  624/1000: dist 0.30 loss 4.80 \n",
      "step  625/1000: dist 0.30 loss 7.59 \n",
      "step  626/1000: dist 0.30 loss 9.10 \n",
      "step  627/1000: dist 0.30 loss 8.84 \n",
      "step  628/1000: dist 0.30 loss 8.35 \n",
      "step  629/1000: dist 0.31 loss 7.26 \n",
      "step  630/1000: dist 0.30 loss 4.57 \n",
      "step  631/1000: dist 0.30 loss 1.69 \n",
      "step  632/1000: dist 0.30 loss 0.69 \n",
      "step  633/1000: dist 0.30 loss 1.75 \n",
      "step  634/1000: dist 0.30 loss 3.36 \n",
      "step  635/1000: dist 0.30 loss 4.01 \n",
      "step  636/1000: dist 0.30 loss 3.38 \n",
      "step  637/1000: dist 0.30 loss 2.57 \n",
      "step  638/1000: dist 0.30 loss 3.09 \n",
      "step  639/1000: dist 0.30 loss 5.89 \n",
      "step  640/1000: dist 0.30 loss 11.91\n",
      "step  641/1000: dist 0.30 loss 22.09\n",
      "step  642/1000: dist 0.30 loss 34.58\n",
      "step  643/1000: dist 0.30 loss 37.51\n",
      "step  644/1000: dist 0.30 loss 21.20\n",
      "step  645/1000: dist 0.30 loss 2.17 \n",
      "step  646/1000: dist 0.30 loss 6.31 \n",
      "step  647/1000: dist 0.30 loss 19.65\n",
      "step  648/1000: dist 0.30 loss 13.66\n",
      "step  649/1000: dist 0.30 loss 1.24 \n",
      "step  650/1000: dist 0.30 loss 7.03 \n",
      "step  651/1000: dist 0.30 loss 13.04\n",
      "step  652/1000: dist 0.30 loss 4.89 \n",
      "step  653/1000: dist 0.29 loss 4.49 \n",
      "step  654/1000: dist 0.30 loss 12.29\n",
      "step  655/1000: dist 0.30 loss 9.99 \n",
      "step  656/1000: dist 0.30 loss 9.71 \n",
      "step  657/1000: dist 0.30 loss 17.31\n",
      "step  658/1000: dist 0.30 loss 15.67\n",
      "step  659/1000: dist 0.30 loss 9.88 \n",
      "step  660/1000: dist 0.30 loss 7.85 \n",
      "step  661/1000: dist 0.30 loss 2.58 \n",
      "step  662/1000: dist 0.30 loss 1.62 \n",
      "step  663/1000: dist 0.30 loss 7.38 \n",
      "step  664/1000: dist 0.30 loss 7.11 \n",
      "step  665/1000: dist 0.30 loss 3.95 \n",
      "step  666/1000: dist 0.30 loss 3.27 \n",
      "step  667/1000: dist 0.30 loss 1.98 \n",
      "step  668/1000: dist 0.30 loss 3.73 \n",
      "step  669/1000: dist 0.30 loss 6.29 \n",
      "step  670/1000: dist 0.30 loss 4.94 \n",
      "step  671/1000: dist 0.30 loss 5.91 \n",
      "step  672/1000: dist 0.30 loss 10.42\n",
      "step  673/1000: dist 0.30 loss 16.02\n",
      "step  674/1000: dist 0.29 loss 24.26\n",
      "step  675/1000: dist 0.30 loss 31.65\n",
      "step  676/1000: dist 0.29 loss 32.83\n",
      "step  677/1000: dist 0.30 loss 25.51\n",
      "step  678/1000: dist 0.30 loss 10.54\n",
      "step  679/1000: dist 0.30 loss 1.28 \n",
      "step  680/1000: dist 0.30 loss 5.72 \n",
      "step  681/1000: dist 0.30 loss 13.81\n",
      "step  682/1000: dist 0.30 loss 14.14\n",
      "step  683/1000: dist 0.29 loss 6.32 \n",
      "step  684/1000: dist 0.30 loss 1.63 \n",
      "step  685/1000: dist 0.29 loss 7.07 \n",
      "step  686/1000: dist 0.30 loss 14.34\n",
      "step  687/1000: dist 0.29 loss 17.52\n",
      "step  688/1000: dist 0.29 loss 21.50\n",
      "step  689/1000: dist 0.30 loss 23.34\n",
      "step  690/1000: dist 0.30 loss 13.72\n",
      "step  691/1000: dist 0.29 loss 4.13 \n",
      "step  692/1000: dist 0.30 loss 7.95 \n",
      "step  693/1000: dist 0.29 loss 13.76\n",
      "step  694/1000: dist 0.29 loss 8.19 \n",
      "step  695/1000: dist 0.29 loss 2.99 \n",
      "step  696/1000: dist 0.29 loss 7.16 \n",
      "step  697/1000: dist 0.29 loss 7.80 \n",
      "step  698/1000: dist 0.29 loss 3.11 \n",
      "step  699/1000: dist 0.29 loss 4.45 \n",
      "step  700/1000: dist 0.29 loss 6.49 \n",
      "step  701/1000: dist 0.29 loss 3.36 \n",
      "step  702/1000: dist 0.29 loss 4.18 \n",
      "step  703/1000: dist 0.29 loss 8.17 \n",
      "step  704/1000: dist 0.29 loss 8.08 \n",
      "step  705/1000: dist 0.29 loss 10.52\n",
      "step  706/1000: dist 0.29 loss 17.43\n",
      "step  707/1000: dist 0.29 loss 18.52\n",
      "step  708/1000: dist 0.29 loss 12.93\n",
      "step  709/1000: dist 0.29 loss 7.10 \n",
      "step  710/1000: dist 0.29 loss 2.64 \n",
      "step  711/1000: dist 0.29 loss 2.74 \n",
      "step  712/1000: dist 0.29 loss 7.96 \n",
      "step  713/1000: dist 0.29 loss 9.53 \n",
      "step  714/1000: dist 0.29 loss 4.87 \n",
      "step  715/1000: dist 0.29 loss 2.97 \n",
      "step  716/1000: dist 0.29 loss 7.12 \n",
      "step  717/1000: dist 0.29 loss 12.72\n",
      "step  718/1000: dist 0.29 loss 17.87\n",
      "step  719/1000: dist 0.29 loss 22.91\n",
      "step  720/1000: dist 0.29 loss 26.68\n",
      "step  721/1000: dist 0.29 loss 23.46\n",
      "step  722/1000: dist 0.29 loss 13.59\n",
      "step  723/1000: dist 0.29 loss 9.42 \n",
      "step  724/1000: dist 0.29 loss 19.38\n",
      "step  725/1000: dist 0.29 loss 30.52\n",
      "step  726/1000: dist 0.29 loss 26.76\n",
      "step  727/1000: dist 0.29 loss 13.86\n",
      "step  728/1000: dist 0.29 loss 7.70 \n",
      "step  729/1000: dist 0.29 loss 8.01 \n",
      "step  730/1000: dist 0.29 loss 8.24 \n",
      "step  731/1000: dist 0.29 loss 9.47 \n",
      "step  732/1000: dist 0.29 loss 10.06\n",
      "step  733/1000: dist 0.29 loss 5.50 \n",
      "step  734/1000: dist 0.29 loss 2.26 \n",
      "step  735/1000: dist 0.29 loss 6.17 \n",
      "step  736/1000: dist 0.29 loss 7.93 \n",
      "step  737/1000: dist 0.29 loss 2.99 \n",
      "step  738/1000: dist 0.29 loss 2.02 \n",
      "step  739/1000: dist 0.28 loss 6.60 \n",
      "step  740/1000: dist 0.29 loss 7.20 \n",
      "step  741/1000: dist 0.29 loss 6.12 \n",
      "step  742/1000: dist 0.29 loss 11.46\n",
      "step  743/1000: dist 0.29 loss 19.38\n",
      "step  744/1000: dist 0.29 loss 23.53\n",
      "step  745/1000: dist 0.29 loss 22.60\n",
      "step  746/1000: dist 0.29 loss 14.87\n",
      "step  747/1000: dist 0.29 loss 4.25 \n",
      "step  748/1000: dist 0.29 loss 2.15 \n",
      "step  749/1000: dist 0.29 loss 8.85 \n",
      "step  750/1000: dist 0.29 loss 11.81\n",
      "step  751/1000: dist 0.29 loss 5.97 \n",
      "step  752/1000: dist 0.29 loss 1.22 \n",
      "step  753/1000: dist 0.29 loss 4.28 \n",
      "step  754/1000: dist 0.28 loss 7.59 \n",
      "step  755/1000: dist 0.28 loss 4.51 \n",
      "step  756/1000: dist 0.28 loss 1.65 \n",
      "step  757/1000: dist 0.28 loss 4.99 \n",
      "step  758/1000: dist 0.28 loss 8.46 \n",
      "step  759/1000: dist 0.28 loss 8.44 \n",
      "step  760/1000: dist 0.28 loss 12.02\n",
      "step  761/1000: dist 0.29 loss 20.58\n",
      "step  762/1000: dist 0.28 loss 25.26\n",
      "step  763/1000: dist 0.28 loss 21.08\n",
      "step  764/1000: dist 0.28 loss 13.27\n",
      "step  765/1000: dist 0.29 loss 8.67 \n",
      "step  766/1000: dist 0.29 loss 12.30\n",
      "step  767/1000: dist 0.28 loss 21.45\n",
      "step  768/1000: dist 0.28 loss 24.26\n",
      "step  769/1000: dist 0.28 loss 15.15\n",
      "step  770/1000: dist 0.28 loss 6.14 \n",
      "step  771/1000: dist 0.29 loss 6.03 \n",
      "step  772/1000: dist 0.29 loss 7.68 \n",
      "step  773/1000: dist 0.29 loss 6.63 \n",
      "step  774/1000: dist 0.28 loss 7.80 \n",
      "step  775/1000: dist 0.29 loss 8.91 \n",
      "step  776/1000: dist 0.28 loss 5.02 \n",
      "step  777/1000: dist 0.29 loss 2.89 \n",
      "step  778/1000: dist 0.28 loss 7.04 \n",
      "step  779/1000: dist 0.29 loss 8.93 \n",
      "step  780/1000: dist 0.29 loss 5.14 \n",
      "step  781/1000: dist 0.28 loss 3.72 \n",
      "step  782/1000: dist 0.28 loss 5.88 \n",
      "step  783/1000: dist 0.28 loss 5.14 \n",
      "step  784/1000: dist 0.28 loss 2.25 \n",
      "step  785/1000: dist 0.29 loss 1.55 \n",
      "step  786/1000: dist 0.28 loss 1.93 \n",
      "step  787/1000: dist 0.29 loss 1.91 \n",
      "step  788/1000: dist 0.29 loss 2.08 \n",
      "step  789/1000: dist 0.29 loss 1.93 \n",
      "step  790/1000: dist 0.29 loss 1.67 \n",
      "step  791/1000: dist 0.28 loss 1.87 \n",
      "step  792/1000: dist 0.29 loss 1.28 \n",
      "step  793/1000: dist 0.28 loss 0.43 \n",
      "step  794/1000: dist 0.29 loss 1.03 \n",
      "step  795/1000: dist 0.28 loss 1.52 \n",
      "step  796/1000: dist 0.29 loss 0.84 \n",
      "step  797/1000: dist 0.28 loss 0.70 \n",
      "step  798/1000: dist 0.29 loss 0.97 \n",
      "step  799/1000: dist 0.29 loss 0.59 \n",
      "step  800/1000: dist 0.28 loss 0.49 \n",
      "step  801/1000: dist 0.28 loss 0.82 \n",
      "step  802/1000: dist 0.28 loss 0.70 \n",
      "step  803/1000: dist 0.28 loss 0.46 \n",
      "step  804/1000: dist 0.28 loss 0.46 \n",
      "step  805/1000: dist 0.28 loss 0.51 \n",
      "step  806/1000: dist 0.28 loss 0.55 \n",
      "step  807/1000: dist 0.28 loss 0.45 \n",
      "step  808/1000: dist 0.28 loss 0.39 \n",
      "step  809/1000: dist 0.28 loss 0.45 \n",
      "step  810/1000: dist 0.28 loss 0.38 \n",
      "step  811/1000: dist 0.28 loss 0.39 \n",
      "step  812/1000: dist 0.28 loss 0.44 \n",
      "step  813/1000: dist 0.28 loss 0.32 \n",
      "step  814/1000: dist 0.28 loss 0.33 \n",
      "step  815/1000: dist 0.28 loss 0.41 \n",
      "step  816/1000: dist 0.28 loss 0.32 \n",
      "step  817/1000: dist 0.28 loss 0.31 \n",
      "step  818/1000: dist 0.28 loss 0.35 \n",
      "step  819/1000: dist 0.28 loss 0.32 \n",
      "step  820/1000: dist 0.28 loss 0.32 \n",
      "step  821/1000: dist 0.28 loss 0.32 \n",
      "step  822/1000: dist 0.28 loss 0.30 \n",
      "step  823/1000: dist 0.28 loss 0.32 \n",
      "step  824/1000: dist 0.28 loss 0.30 \n",
      "step  825/1000: dist 0.28 loss 0.30 \n",
      "step  826/1000: dist 0.28 loss 0.30 \n",
      "step  827/1000: dist 0.28 loss 0.30 \n",
      "step  828/1000: dist 0.28 loss 0.29 \n",
      "step  829/1000: dist 0.28 loss 0.29 \n",
      "step  830/1000: dist 0.28 loss 0.30 \n",
      "step  831/1000: dist 0.28 loss 0.29 \n",
      "step  832/1000: dist 0.28 loss 0.29 \n",
      "step  833/1000: dist 0.28 loss 0.29 \n",
      "step  834/1000: dist 0.28 loss 0.28 \n",
      "step  835/1000: dist 0.28 loss 0.29 \n",
      "step  836/1000: dist 0.28 loss 0.28 \n",
      "step  837/1000: dist 0.28 loss 0.29 \n",
      "step  838/1000: dist 0.28 loss 0.29 \n",
      "step  839/1000: dist 0.28 loss 0.28 \n",
      "step  840/1000: dist 0.28 loss 0.29 \n",
      "step  841/1000: dist 0.28 loss 0.28 \n",
      "step  842/1000: dist 0.28 loss 0.28 \n",
      "step  843/1000: dist 0.28 loss 0.28 \n",
      "step  844/1000: dist 0.28 loss 0.29 \n",
      "step  845/1000: dist 0.28 loss 0.29 \n",
      "step  846/1000: dist 0.28 loss 0.28 \n",
      "step  847/1000: dist 0.28 loss 0.28 \n",
      "step  848/1000: dist 0.28 loss 0.28 \n",
      "step  849/1000: dist 0.28 loss 0.28 \n",
      "step  850/1000: dist 0.28 loss 0.28 \n",
      "step  851/1000: dist 0.28 loss 0.28 \n",
      "step  852/1000: dist 0.28 loss 0.28 \n",
      "step  853/1000: dist 0.28 loss 0.28 \n",
      "step  854/1000: dist 0.28 loss 0.28 \n",
      "step  855/1000: dist 0.28 loss 0.28 \n",
      "step  856/1000: dist 0.28 loss 0.28 \n",
      "step  857/1000: dist 0.28 loss 0.28 \n",
      "step  858/1000: dist 0.28 loss 0.28 \n",
      "step  859/1000: dist 0.28 loss 0.28 \n",
      "step  860/1000: dist 0.28 loss 0.28 \n",
      "step  861/1000: dist 0.28 loss 0.28 \n",
      "step  862/1000: dist 0.28 loss 0.28 \n",
      "step  863/1000: dist 0.28 loss 0.28 \n",
      "step  864/1000: dist 0.28 loss 0.28 \n",
      "step  865/1000: dist 0.28 loss 0.28 \n",
      "step  866/1000: dist 0.28 loss 0.28 \n",
      "step  867/1000: dist 0.28 loss 0.28 \n",
      "step  868/1000: dist 0.28 loss 0.28 \n",
      "step  869/1000: dist 0.28 loss 0.28 \n",
      "step  870/1000: dist 0.28 loss 0.28 \n",
      "step  871/1000: dist 0.28 loss 0.28 \n",
      "step  872/1000: dist 0.28 loss 0.28 \n",
      "step  873/1000: dist 0.28 loss 0.28 \n",
      "step  874/1000: dist 0.28 loss 0.28 \n",
      "step  875/1000: dist 0.28 loss 0.28 \n",
      "step  876/1000: dist 0.28 loss 0.28 \n",
      "step  877/1000: dist 0.28 loss 0.28 \n",
      "step  878/1000: dist 0.28 loss 0.28 \n",
      "step  879/1000: dist 0.28 loss 0.28 \n",
      "step  880/1000: dist 0.28 loss 0.28 \n",
      "step  881/1000: dist 0.28 loss 0.28 \n",
      "step  882/1000: dist 0.28 loss 0.28 \n",
      "step  883/1000: dist 0.28 loss 0.28 \n",
      "step  884/1000: dist 0.28 loss 0.28 \n",
      "step  885/1000: dist 0.28 loss 0.28 \n",
      "step  886/1000: dist 0.28 loss 0.28 \n",
      "step  887/1000: dist 0.28 loss 0.28 \n",
      "step  888/1000: dist 0.28 loss 0.28 \n",
      "step  889/1000: dist 0.28 loss 0.28 \n",
      "step  890/1000: dist 0.28 loss 0.28 \n",
      "step  891/1000: dist 0.28 loss 0.28 \n",
      "step  892/1000: dist 0.28 loss 0.28 \n",
      "step  893/1000: dist 0.28 loss 0.28 \n",
      "step  894/1000: dist 0.28 loss 0.28 \n",
      "step  895/1000: dist 0.28 loss 0.28 \n",
      "step  896/1000: dist 0.28 loss 0.28 \n",
      "step  897/1000: dist 0.28 loss 0.28 \n",
      "step  898/1000: dist 0.28 loss 0.28 \n",
      "step  899/1000: dist 0.28 loss 0.28 \n",
      "step  900/1000: dist 0.28 loss 0.28 \n",
      "step  901/1000: dist 0.28 loss 0.28 \n",
      "step  902/1000: dist 0.28 loss 0.28 \n",
      "step  903/1000: dist 0.27 loss 0.27 \n",
      "step  904/1000: dist 0.27 loss 0.27 \n",
      "step  905/1000: dist 0.27 loss 0.27 \n",
      "step  906/1000: dist 0.28 loss 0.28 \n",
      "step  907/1000: dist 0.28 loss 0.28 \n",
      "step  908/1000: dist 0.27 loss 0.27 \n",
      "step  909/1000: dist 0.27 loss 0.27 \n",
      "step  910/1000: dist 0.27 loss 0.27 \n",
      "step  911/1000: dist 0.27 loss 0.27 \n",
      "step  912/1000: dist 0.27 loss 0.27 \n",
      "step  913/1000: dist 0.27 loss 0.27 \n",
      "step  914/1000: dist 0.27 loss 0.27 \n",
      "step  915/1000: dist 0.27 loss 0.27 \n",
      "step  916/1000: dist 0.27 loss 0.27 \n",
      "step  917/1000: dist 0.27 loss 0.27 \n",
      "step  918/1000: dist 0.27 loss 0.27 \n",
      "step  919/1000: dist 0.27 loss 0.27 \n",
      "step  920/1000: dist 0.27 loss 0.27 \n",
      "step  921/1000: dist 0.27 loss 0.27 \n",
      "step  922/1000: dist 0.27 loss 0.27 \n",
      "step  923/1000: dist 0.27 loss 0.27 \n",
      "step  924/1000: dist 0.27 loss 0.27 \n",
      "step  925/1000: dist 0.27 loss 0.27 \n",
      "step  926/1000: dist 0.27 loss 0.27 \n",
      "step  927/1000: dist 0.27 loss 0.27 \n",
      "step  928/1000: dist 0.27 loss 0.27 \n",
      "step  929/1000: dist 0.27 loss 0.27 \n",
      "step  930/1000: dist 0.27 loss 0.27 \n",
      "step  931/1000: dist 0.27 loss 0.27 \n",
      "step  932/1000: dist 0.27 loss 0.27 \n",
      "step  933/1000: dist 0.27 loss 0.27 \n",
      "step  934/1000: dist 0.27 loss 0.27 \n",
      "step  935/1000: dist 0.27 loss 0.27 \n",
      "step  936/1000: dist 0.27 loss 0.27 \n",
      "step  937/1000: dist 0.27 loss 0.27 \n",
      "step  938/1000: dist 0.27 loss 0.27 \n",
      "step  939/1000: dist 0.27 loss 0.27 \n",
      "step  940/1000: dist 0.27 loss 0.27 \n",
      "step  941/1000: dist 0.27 loss 0.27 \n",
      "step  942/1000: dist 0.27 loss 0.27 \n",
      "step  943/1000: dist 0.27 loss 0.27 \n",
      "step  944/1000: dist 0.27 loss 0.27 \n",
      "step  945/1000: dist 0.27 loss 0.27 \n",
      "step  946/1000: dist 0.27 loss 0.27 \n",
      "step  947/1000: dist 0.27 loss 0.27 \n",
      "step  948/1000: dist 0.27 loss 0.27 \n",
      "step  949/1000: dist 0.27 loss 0.27 \n",
      "step  950/1000: dist 0.27 loss 0.27 \n",
      "step  951/1000: dist 0.27 loss 0.27 \n",
      "step  952/1000: dist 0.27 loss 0.27 \n",
      "step  953/1000: dist 0.27 loss 0.27 \n",
      "step  954/1000: dist 0.27 loss 0.27 \n",
      "step  955/1000: dist 0.27 loss 0.27 \n",
      "step  956/1000: dist 0.27 loss 0.27 \n",
      "step  957/1000: dist 0.27 loss 0.27 \n",
      "step  958/1000: dist 0.27 loss 0.27 \n",
      "step  959/1000: dist 0.27 loss 0.27 \n",
      "step  960/1000: dist 0.27 loss 0.27 \n",
      "step  961/1000: dist 0.27 loss 0.27 \n",
      "step  962/1000: dist 0.27 loss 0.27 \n",
      "step  963/1000: dist 0.27 loss 0.27 \n",
      "step  964/1000: dist 0.27 loss 0.27 \n",
      "step  965/1000: dist 0.27 loss 0.27 \n",
      "step  966/1000: dist 0.27 loss 0.27 \n",
      "step  967/1000: dist 0.27 loss 0.27 \n",
      "step  968/1000: dist 0.27 loss 0.27 \n",
      "step  969/1000: dist 0.27 loss 0.27 \n",
      "step  970/1000: dist 0.27 loss 0.27 \n",
      "step  971/1000: dist 0.27 loss 0.27 \n",
      "step  972/1000: dist 0.27 loss 0.27 \n",
      "step  973/1000: dist 0.27 loss 0.27 \n",
      "step  974/1000: dist 0.27 loss 0.27 \n",
      "step  975/1000: dist 0.27 loss 0.27 \n",
      "step  976/1000: dist 0.27 loss 0.27 \n",
      "step  977/1000: dist 0.27 loss 0.27 \n",
      "step  978/1000: dist 0.27 loss 0.27 \n",
      "step  979/1000: dist 0.27 loss 0.27 \n",
      "step  980/1000: dist 0.27 loss 0.27 \n",
      "step  981/1000: dist 0.27 loss 0.27 \n",
      "step  982/1000: dist 0.27 loss 0.27 \n",
      "step  983/1000: dist 0.27 loss 0.27 \n",
      "step  984/1000: dist 0.27 loss 0.27 \n",
      "step  985/1000: dist 0.27 loss 0.27 \n",
      "step  986/1000: dist 0.27 loss 0.27 \n",
      "step  987/1000: dist 0.27 loss 0.27 \n",
      "step  988/1000: dist 0.27 loss 0.27 \n",
      "step  989/1000: dist 0.27 loss 0.27 \n",
      "step  990/1000: dist 0.27 loss 0.27 \n",
      "step  991/1000: dist 0.27 loss 0.27 \n",
      "step  992/1000: dist 0.27 loss 0.27 \n",
      "step  993/1000: dist 0.27 loss 0.27 \n",
      "step  994/1000: dist 0.27 loss 0.27 \n",
      "step  995/1000: dist 0.27 loss 0.27 \n",
      "step  996/1000: dist 0.27 loss 0.27 \n",
      "step  997/1000: dist 0.27 loss 0.27 \n",
      "step  998/1000: dist 0.27 loss 0.27 \n",
      "step  999/1000: dist 0.27 loss 0.27 \n",
      "step 1000/1000: dist 0.27 loss 0.27 \n",
      "Elapsed: 84.2 s\n"
     ]
    }
   ],
   "source": [
    "# HIDE OUTPUT\n",
    "cmd = f\"python /content/stylegan2-ada-pytorch/projector.py \"\\\n",
    "  f\"--save-video 0 --num-steps 1000 --outdir=out_target \"\\\n",
    "  f\"--target=cropped_target.png --network={NETWORK}\"\n",
    "!{cmd}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CXuqLpfb98D7"
   },
   "source": [
    "With the conversion complete, lets have a look at the two GANs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 281
    },
    "id": "CTiPS-Zu-ybP",
    "outputId": "23c78670-f780-4fca-8f25-3d8266bce1a3"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img_gan_source = cv2.imread('/content/out_source/proj.png')\n",
    "img = cv2.cvtColor(img_gan_source, cv2.COLOR_BGR2RGB)\n",
    "plt.imshow(img)\n",
    "plt.title('source-gan')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 281
    },
    "id": "T9b10Ejn_bIZ",
    "outputId": "4ef0b069-087d-43fa-d84c-64fa2f76f1c2"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img_gan_target = cv2.imread('/content/out_target/proj.png')\n",
    "img = cv2.cvtColor(img_gan_target, cv2.COLOR_BGR2RGB)\n",
    "plt.imshow(img)\n",
    "plt.title('target-gan')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3rkmzXIEgSKp"
   },
   "source": [
    "As you can see, the two GAN-generated images look similar to their real-world counterparts. However, they are by no means exact replicas.\n",
    "\n",
    "## Build the Video\n",
    "\n",
    "The following code builds a transition video between the two latent vectors previously obtained."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 84,
     "referenced_widgets": [
      "e4545b4cffb0477a9cc813c1f13903e4",
      "e3fd917dcbf24407ac7e0fce4ad9aa55",
      "57a27f96e498445093afa43dd956676a",
      "60a0e3008b5d462296c897a8b3454e21",
      "6a16fca61c7d45fe83daa5b4d520643b",
      "6cb4138efc9347b685ba60a3848d1a46",
      "ea48cdd354e941fda06f759099494c0b",
      "32963d33071242389e5ea2e64a4890e4",
      "22ed8465595d49139efd15c94e493c2a",
      "3b6b91260e794a10aacae2e42754ad57",
      "8604e203fd904a7a90145780702ee913"
     ]
    },
    "id": "KX9J5-t-spyy",
    "outputId": "69896c16-87bd-4de5-8e6e-0f6fb7b1ca41"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e4545b4cffb0477a9cc813c1f13903e4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/150 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Setting up PyTorch plugin \"bias_act_plugin\"... Done.\n",
      "Setting up PyTorch plugin \"upfirdn2d_plugin\"... Done.\n"
     ]
    }
   ],
   "source": [
    "# HIDE OUTPUT\n",
    "import torch\n",
    "import dnnlib\n",
    "import legacy\n",
    "import PIL.Image\n",
    "import numpy as np\n",
    "import imageio\n",
    "from tqdm.notebook import tqdm\n",
    "\n",
    "lvec1 = np.load('/content/out_source/projected_w.npz')['w']\n",
    "lvec2 = np.load('/content/out_target/projected_w.npz')['w']\n",
    "\n",
    "network_pkl = \"https://nvlabs-fi-cdn.nvidia.com/stylegan2\"\\\n",
    "  \"-ada-pytorch/pretrained/ffhq.pkl\"\n",
    "device = torch.device('cuda')\n",
    "with dnnlib.util.open_url(network_pkl) as fp:\n",
    "    G = legacy.load_network_pkl(fp)['G_ema']\\\n",
    "      .requires_grad_(False).to(device) \n",
    "\n",
    "diff = lvec2 - lvec1\n",
    "step = diff / STEPS\n",
    "current = lvec1.copy()\n",
    "target_uint8 = np.array([1024,1024,3], dtype=np.uint8)\n",
    "\n",
    "video = imageio.get_writer('/content/movie.mp4', mode='I', fps=FPS, \n",
    "                           codec='libx264', bitrate='16M')\n",
    "\n",
    "for j in tqdm(range(STEPS)):\n",
    "  z = torch.from_numpy(current).to(device)\n",
    "  synth_image = G.synthesis(z, noise_mode='const')\n",
    "  synth_image = (synth_image + 1) * (255/2)\n",
    "  synth_image = synth_image.permute(0, 2, 3, 1).clamp(0, 255)\\\n",
    "    .to(torch.uint8)[0].cpu().numpy()\n",
    "\n",
    "  repeat = FREEZE_STEPS if j==0 or j==(STEPS-1) else 1\n",
    "   \n",
    "  for i in range(repeat):\n",
    "    video.append_data(synth_image)\n",
    "  current = current + step\n",
    "\n",
    "\n",
    "video.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qeZYEKrlfJYn"
   },
   "source": [
    "## Download your Video\n",
    "\n",
    "If you made it through all of these steps, you are now ready to download your video."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 17
    },
    "id": "moF7jia2fPv0",
    "outputId": "6d7c2fe8-3c1e-4a8a-9e28-c2fbe0fd2520"
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "    async function download(id, filename, size) {\n",
       "      if (!google.colab.kernel.accessAllowed) {\n",
       "        return;\n",
       "      }\n",
       "      const div = document.createElement('div');\n",
       "      const label = document.createElement('label');\n",
       "      label.textContent = `Downloading \"${filename}\": `;\n",
       "      div.appendChild(label);\n",
       "      const progress = document.createElement('progress');\n",
       "      progress.max = size;\n",
       "      div.appendChild(progress);\n",
       "      document.body.appendChild(div);\n",
       "\n",
       "      const buffers = [];\n",
       "      let downloaded = 0;\n",
       "\n",
       "      const channel = await google.colab.kernel.comms.open(id);\n",
       "      // Send a message to notify the kernel that we're ready.\n",
       "      channel.send({})\n",
       "\n",
       "      for await (const message of channel.messages) {\n",
       "        // Send a message to notify the kernel that we're ready.\n",
       "        channel.send({})\n",
       "        if (message.buffers) {\n",
       "          for (const buffer of message.buffers) {\n",
       "            buffers.push(buffer);\n",
       "            downloaded += buffer.byteLength;\n",
       "            progress.value = downloaded;\n",
       "          }\n",
       "        }\n",
       "      }\n",
       "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
       "      const a = document.createElement('a');\n",
       "      a.href = window.URL.createObjectURL(blob);\n",
       "      a.download = filename;\n",
       "      div.appendChild(a);\n",
       "      a.click();\n",
       "      div.remove();\n",
       "    }\n",
       "  "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "download(\"download_896dabce-324e-4402-b1a8-ffd8a925d21c\", \"movie.mp4\", 17037294)"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# HIDE OUTPUT\n",
    "from google.colab import files\n",
    "files.download(\"movie.mp4\") "
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "Copy of new_t81_558_class_09_4_facial_points.ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "22ed8465595d49139efd15c94e493c2a": {
     "model_module": "@jupyter-widgets/base",
     "model_module_version": "1.2.0",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "32963d33071242389e5ea2e64a4890e4": {
     "model_module": "@jupyter-widgets/controls",
     "model_module_version": "1.5.0",
     "model_name": "ProgressStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "ProgressStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "bar_color": null,
      "description_width": ""
     }
    },
    "3b6b91260e794a10aacae2e42754ad57": {
     "model_module": "@jupyter-widgets/controls",
     "model_module_version": "1.5.0",
     "model_name": "DescriptionStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DescriptionStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": ""
     }
    },
    "57a27f96e498445093afa43dd956676a": {
     "model_module": "@jupyter-widgets/controls",
     "model_module_version": "1.5.0",
     "model_name": "HTMLModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HTMLModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HTMLView",
      "description": "",
      "description_tooltip": null,
      "layout": "IPY_MODEL_ea48cdd354e941fda06f759099494c0b",
      "placeholder": "​",
      "style": "IPY_MODEL_6cb4138efc9347b685ba60a3848d1a46",
      "value": "100%"
     }
    },
    "60a0e3008b5d462296c897a8b3454e21": {
     "model_module": "@jupyter-widgets/controls",
     "model_module_version": "1.5.0",
     "model_name": "FloatProgressModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "FloatProgressModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "ProgressView",
      "bar_style": "success",
      "description": "",
      "description_tooltip": null,
      "layout": "IPY_MODEL_22ed8465595d49139efd15c94e493c2a",
      "max": 150,
      "min": 0,
      "orientation": "horizontal",
      "style": "IPY_MODEL_32963d33071242389e5ea2e64a4890e4",
      "value": 150
     }
    },
    "6a16fca61c7d45fe83daa5b4d520643b": {
     "model_module": "@jupyter-widgets/controls",
     "model_module_version": "1.5.0",
     "model_name": "HTMLModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HTMLModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HTMLView",
      "description": "",
      "description_tooltip": null,
      "layout": "IPY_MODEL_8604e203fd904a7a90145780702ee913",
      "placeholder": "​",
      "style": "IPY_MODEL_3b6b91260e794a10aacae2e42754ad57",
      "value": " 150/150 [00:09&lt;00:00, 21.29it/s]"
     }
    },
    "6cb4138efc9347b685ba60a3848d1a46": {
     "model_module": "@jupyter-widgets/controls",
     "model_module_version": "1.5.0",
     "model_name": "DescriptionStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DescriptionStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": ""
     }
    },
    "8604e203fd904a7a90145780702ee913": {
     "model_module": "@jupyter-widgets/base",
     "model_module_version": "1.2.0",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "e3fd917dcbf24407ac7e0fce4ad9aa55": {
     "model_module": "@jupyter-widgets/base",
     "model_module_version": "1.2.0",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "e4545b4cffb0477a9cc813c1f13903e4": {
     "model_module": "@jupyter-widgets/controls",
     "model_module_version": "1.5.0",
     "model_name": "HBoxModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HBoxModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HBoxView",
      "box_style": "",
      "children": [
       "IPY_MODEL_57a27f96e498445093afa43dd956676a",
       "IPY_MODEL_60a0e3008b5d462296c897a8b3454e21",
       "IPY_MODEL_6a16fca61c7d45fe83daa5b4d520643b"
      ],
      "layout": "IPY_MODEL_e3fd917dcbf24407ac7e0fce4ad9aa55"
     }
    },
    "ea48cdd354e941fda06f759099494c0b": {
     "model_module": "@jupyter-widgets/base",
     "model_module_version": "1.2.0",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
